AARNE VARTIA
Acta Universitatis Tamperensis 2154
Continuous-Equivalent Urea Clearances EKR and stdK as Dose Measures in Intermittent Hemodialysis AARNE VARTIA
Continuous-Equivalent Urea Clearances
EKR and stdK as Dose Measures
in Intermittent Hemodialysis
AUT 2154
AARNE VARTIA
Continuous-Equivalent Urea Clearances
EKR and stdK as Dose Measures
in Intermittent Hemodialysis
ACADEMIC DISSERTATION
To be presented, with the permission of
the Board of the School of Medicine of the University of Tampere,
for public discussion in the small auditorium of building M,
Pirkanmaa Hospital District, Teiskontie 35, Tampere,
on 22 April 2016, at 12 o’clock.
UNIVERSITY OF TAMPERE
AARNE VARTIA
Continuous-Equivalent Urea Clearances
EKR and stdK as Dose Measures
in Intermittent Hemodialysis
Acta Universitatis Tamperensis 2154
Tampere University Press
Tampere 2016
ACADEMIC DISSERTATION
University of Tampere, School of Medicine
Savonlinna Central Hospital
Finland
Supervised by
Professor emeritus Jukka Mustonen
University of Tampere
Finland
Reviewed by
Docent Risto Ikäheimo
University of Oulu
Finland
Docent Kaj Metsärinne
University of Helsinki
University of Turku
Finland
The originality of this thesis has been checked using the Turnitin OriginalityCheck service
in accordance with the quality management system of the University of Tampere.
Copyright ©2016 Tampere University Press and the author
Cover design by
Mikko Reinikka
Distributor:
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Acta Universitatis Tamperensis 2154
ISBN 978-952-03-0082-1 (print)
ISSN-L 1455-1616
ISSN 1455-1616
Acta Electronica Universitatis Tamperensis 1653
ISBN 978-952-03-0083-8 (pdf )
ISSN 1456-954X
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Suomen Yliopistopaino Oy – Juvenes Print
Tampere 2016
441 729
Painotuote
Dedicated to my wife Ansa, a Very Important Person
CONTENTS
Abstract ........................................................................................................................................ 8
Tiivistelmä ................................................................................................................................. 11
LIST OF ORIGINAL COMMUNICATIONS ................................................................. 15
ABBREVIATIONS AND DEFINITIONS ....................................................................... 16
1
INTRODUCTION ........................................................................................................ 18
2
REVIEW OF THE LITERATURE ........................................................................... 20
2.1 Uremic syndrome ................................................................................................ 20
2.1.1 Water and sodium .................................................................................... 20
2.1.2 Acidosis ..................................................................................................... 21
2.1.3 Anemia and endocrine disturbances ..................................................... 21
2.1.4 Urea ............................................................................................................ 21
2.1.5 Uremic toxins ........................................................................................... 22
2.1.6 Causes of death ........................................................................................ 24
2.2 Blood purification techniques ............................................................................ 24
2.2.1 Diffusion and convection ....................................................................... 24
2.2.2 Adsorption and ion exchange ................................................................ 25
2.3 Hemodialysis prescription .................................................................................. 25
2.3.1 Dialysate composition and temperature............................................... 25
2.3.2 Filter and convection technique ............................................................ 25
2.3.3 Blood, dialysate, and filtrate flow .......................................................... 26
2.3.4 Duration and frequency .......................................................................... 27
2.3.5 Water removal .......................................................................................... 27
2.3.6 Prescribed and delivered dose................................................................ 27
2.4 Delivered dose...................................................................................................... 29
2.4.1 Marker solutes .......................................................................................... 29
2.4.2 Concentration and clearance .................................................................. 30
2.4.3 Single-pool UKM ..................................................................................... 30
2.4.4 Double-pool UKM .................................................................................. 32
2.4.5 eKt/V ........................................................................................................ 34
2.4.6 Direct dialysis quantification (DDQ).................................................... 35
2.4.7 Online monitoring ................................................................................... 35
2.4.8 Residual renal function............................................................................ 36
2.5
2.6
Continuous-equivalent clearance (ECC) .......................................................... 37
2.5.1 Aiming at a universal dose measure ...................................................... 37
2.5.2 Definitions based on UKM .................................................................... 37
2.5.3 Simple equations ...................................................................................... 39
2.5.4 Guidelines ................................................................................................. 40
Dependence of outcome on dose (adequacy) ................................................. 40
2.6.1 Session dose .............................................................................................. 40
2.6.2 Treatment duration .................................................................................. 41
2.6.3 Treatment frequency ............................................................................... 42
2.6.4 Scaling ........................................................................................................ 44
2.6.5 Residual renal function ........................................................................... 45
2.6.6 Continuous-equivalent clearance ........................................................... 45
2.6.7 Overdialysis ............................................................................................... 46
2.6.8 Soft endpoints .......................................................................................... 47
3
AIMS OF THE STUDY ............................................................................................... 49
3.1 Is high mortality in hemodialysis due to low dose?........................................ 49
3.2 How should the dialysis dose be measured? ................................................... 49
3.3 How could dosing be improved? ...................................................................... 49
4
SUBJECTS AND METHODS .................................................................................... 50
4.1 Patients .................................................................................................................. 50
4.1.1 Hemodialysis treatment periods and modeling sessions ................... 50
4.1.2 Dialysis prescriptions .............................................................................. 52
4.1.3 Data collection ......................................................................................... 52
4.2 Calculations........................................................................................................... 52
4.2.1 Urea kinetic modeling ............................................................................. 52
4.2.2 Simulation and automation .................................................................... 54
4.2.3 HEMO-equivalent EKR/V and stdK/V ............................................ 54
4.2.4 Anthropometric normalization of ECC ............................................... 55
4.3 Computer applications ........................................................................................ 55
4.4 Statistical methods ............................................................................................... 56
4.5 Ethical aspects ...................................................................................................... 56
5
RESULTS ......................................................................................................................... 57
5.1 Effect of frequency (I FREQUENCY) ........................................................... 57
5.1.1 Effect on measures of dialysis dose ...................................................... 57
5.1.2 Effect on required treatment time ........................................................ 58
5.1.3 Effect on concentrations ........................................................................ 59
5.2
5.3
5.4
5.5
Effect of residual renal function (II INCREMENTAL) .............................. 61
5.2.1 Effect on required treatment time ........................................................ 61
5.2.2 Effect on concentrations ........................................................................ 62
5.2.3 Contribution to urea removal ................................................................ 64
Equivalent doses (III EQUIVALENCY) ....................................................... 65
5.3.1 ECC corresponding to HEMO standard dose ................................... 65
5.3.2 Dialyzing to HEMO-equivalent ECC .................................................. 66
5.3.3 Solutes with different kinetics ................................................................ 67
Creating the prescription (IV AUTOMATION) ........................................... 71
5.4.1 Prescribed and delivered dose................................................................ 71
5.4.2 Optimization procedure.......................................................................... 71
5.4.3 Automatic prescriptions.......................................................................... 72
Prognostic value (V ADEQUACY) ................................................................. 75
5.5.1 Association of ECC with death risk ..................................................... 75
5.5.2 Interaction between nPCR and ECC.................................................... 76
5.5.3 Association of ECC and mortality with gender .................................. 79
6
DISCUSSION ................................................................................................................. 80
6.1 Urea kinetic modeling ......................................................................................... 80
6.2 Continuous-equivalent urea clearance .............................................................. 81
6.3 Scaling .................................................................................................................... 82
6.4 Protein catabolic rate and dialysis dose ............................................................ 83
6.5 Treatment duration and frequency ................................................................... 84
6.6 Residual renal function ....................................................................................... 85
6.7 Solutes with different kinetics............................................................................ 85
6.8 Adequacy ............................................................................................................... 87
6.9 Limitations ............................................................................................................ 88
6.10 New questions ...................................................................................................... 88
7
CONCLUSIONS ............................................................................................................ 90
7.1 Is high mortality in hemodialysis due to low dose?........................................ 90
7.2 How should the dialysis dose be measured? ................................................... 90
7.3 How could dosing be improved? ...................................................................... 91
8
UKM EQUATIONS...................................................................................................... 92
9
ACKNOWLEDGEMENTS ........................................................................................ 95
10
REFERENCES ............................................................................................................... 96
ORIGINAL COMMUNICATIONS ................................................................................. 117
Abstract
Continuous-Equivalent Urea Clearances EKR and stdK as Dose
Measures in Intermittent Hemodialysis
Background
Survival of hemodialysis patients is associated with the treatment dose in numerous
large observational studies, but no statistically significant cause and effect
relationship has been confirmed in randomized clinical trials.
How to measure the hemodialysis dose has been debated for decades. Urea is
not a good representative of uremic toxins and its concentration does not reflect
the severity of uremia.
In the conventional thrice weekly schedule, estimates of the volume cleared in a
single hemodialysis session predict survival better than urea concentration, but they
cannot be used in comparing dosing in different schedules. Positive outcomes have
been reported from frequent (“daily”) hemodialysis, but whether this is due to
more efficient toxin removal or other factors remains unknown. In many studies
the role of residual renal function (RRF) has been ignored, although it has a
profound effect on outcome. Scaling of dose by urea distribution volume may be
unsatisfactory.
Methods
In metabolic equilibrium urea removal rate E is equal to its generation rate G.
Continuous-equivalent clearance (ECC) is a simple concept based on the definition
of clearance:
ECC = G / C,
where C is the reference concentration: time-averaged concentration TAC in EKR,
average predialysis concentration PAC in stdK. G, TAC, and PAC are derived
from the urea kinetic model (UKM). ECC takes into consideration the schedule
and includes RRF.
8
Abstract
In the present thesis the characteristics of ECCs were investigated by computer
simulations based on data derived from 1,200 urea kinetic modeling sessions
among 51 patients. A method to create an optimized dialysis prescription
automatically using a computer was also developed and the associations of
different ECC values with death risk compared using statistical methods.
Results
1) Residual renal function contributes significantly to urea removal and even more
to the removal of true uremic toxins. The ECC concept is a rational way to
address RRF. Incremental dialysis relieves the burden of the treatment.
2) Increasing frequency with constant weekly treatment time and dialyzer clearance
decreases TAC and PAC and increases EKR and stdK. stdK is more sensitive
to frequency and RRF than EKR.
3) With a constant EKR target, increasing frequency decreases PAC. With a
constant stdK target, increasing frequency increases TAC.
4) The EKR/V and stdK/V values corresponding to eKt/V 1.20 in a
conventional 3 x 4 h/week schedule were 3.44 and 2.40/week.
5) The dialysis dose can be adjusted for protein catabolic rate by reducing high
urea concentrations. A prescription fulfilling multiple criteria can be created
automatically by a computer. ECCs are required for optimizing frequency, time,
and concentrations.
6) EKR is significantly associated with mortality in the present material, while
stdK is not. Protein catabolic rate (PCR) and dialysis dose seem to have a
synergistic association with survival.
7) Urea and β2-microglobulin react similarly to changes in time and frequency, but
differently to changes in blood and dialysate flow (Qb, Qd). Clearance of urea is
heavily flow-dependent, that of β2-microglobulin is not. With equal urea
clearance (EKR) or concentration (TAC), concentration of β2-microglobulin is
lower with more gentle treatment (lower Qb and Qd and longer treatment
time).
Abstract
9
Conclusions
No single absolutely correct dialysis dose measure can be said to exist. Urea has
exceptional kinetics which does not universally describe the behavior of uremic
toxins. The outcomes probably cannot be improved by raising urea removal above
the current level.
A distinction must be made between dose and effect. The continuousequivalent clearances EKR/V and stdK/V are patient-dependent measures of the
effect of dialysis on urea concentrations. They handle treatment frequency and
RRF appropriately, but are not ideal determinants of treatment adequacy when
based solely on urea kinetics.
The delivered dialysis dose can be defined technically as weekly dialyzer urea
clearance normalized with body surface area (nKturea), e.g. 180 L/week/1.73m2
corresponding to about 14 mL/min of EKR, 3.6/week of EKR/V and 2.4/week
of stdK/V in a 3 x 4 h/week schedule. This guarantees sufficient removal of easily
dialyzable retention solutes. The target can be safely reduced by the normalized
renal urea clearance (nKrurea, L/week/1.73 m2). Kt can be easily measured with an
online ionic dialysance monitor, but weekly nKt is not equal to continuous
clearance. Dialyzer clearance and weekly treatment time determine the delivered
dose, reflecting consumption of resources. Blood samples, UKM and computers
are not needed. ECC, Kt/V and URR are indirect measures of delivered dose.
Future investigations with constant dose (weekly nKt) will hopefully reveal the
best strategies (time, frequency or convection) to control the long-term effects of
uremic toxins. Dialyzer urea clearance multiplied by treatment time is not enough
to define dialysis dosing. It cannot be described with only one number; at least four
are required: weekly dose, convection volume, duration and frequency. Dose,
dosing and adequacy are different things.
10
Abstract
Tiivistelmä
Urean vakiopuhdistumat EKR ja stdK jaksottaisen keinomunuaishoidon annosmittoina
Keinomunuaishoidolla tarkoitetaan menetelmiä, joilla verestä poistetaan ulkoisen
laitteen (artificial kidney) avulla munuaisten toiminnanvajauksessa kertyviä haitallisia aineita (uremic toxins). Yleisesti käytettyä luontevaa englanninkielistä vastinetta
keinomunuaishoito-sanalle ei ole. Useimmiten käytetään sanoja hemodialysis tai
blood purification.
Vakiopuhdistuma (continuous-equivalent clearance, ECC) ja mallinnushoito
(urea kinetic modeling session) eivät ole vakiintuneita suomen kielen sanoja.
Tausta
Laajoissa havainnoivissa tutkimuksissa keinomunuaispotilaitten menestymisellä on
yhteys hoitoannokseen, mutta satunnaistetuissa kliinisissä hoitokokeissa syyseuraussuhdetta ei ole kyetty varmistamaan.
Keinomunuaishoidon annoksen mittaamisesta on kiistelty vuosikymmeniä. Virtsa-aine (urea) ei ole sopiva edustamaan munuaisten toiminnanvajauksessa kertyviä
haitallisia aineita (ureemisia toksiineja) eikä sen pitoisuus kuvasta munuaisten toiminnanvajauksen vaikeusastetta.
Tavanomaisessa hoitokaaviossa yksittäisessä keinomunuaishoidossa puhdistunut
nestemäärä ennakoi potilaan menestymistä paremmin kuin ureapitoisuus, mutta sitä
ei voi käyttää erilaisten hoitokaavioiden vertailussa. Tiheällä (“päivittäisellä”) hoidolla on saavutettu myönteisiä tuloksia, mutta on epäselvää, johtuvatko ne ureemisten toksiinien tehokkaammasta poistamisesta vai muista tekijöistä. Monissa tutkimuksissa jäljellä oleva munuaistoiminta (RRF) on jätetty huomiotta, vaikka se vaikuttaa merkittävästi hoitotuloksiin. Puhdistuman suhteuttaminen urean jakautumistilavuuteen on epätyydyttävä normalisointimenetelmä, josta kärsivät erityisesti naiset ja lapset.
Tiivistelmä
11
Menetelmät
Aineenvaihdunnan ollessa tasapainossa urean poistumisnopeus E on yhtä suuri
kuin sen syntymisnopeus G. Vakiopuhdistuma (ECC) perustuu puhdistuman määritelmään:
ECC = G / C,
missä C on viitepitoisuus: aikapainotettu keskipitoisuus TAC tai keskimääräinen
huippupitoisuus PAC. G, TAC ja PAC määritetään ureakineettisellä mallilla
(UKM). Vakiopuhdistuma ottaa huomioon hoitotiheyden ja sisältää jäljellä olevan
munuaistoiminnan.
Väitöskirjatyössä selvitettiin vakiopuhdistumien ominaisuuksia tietokonemalleilla perustuen 51 potilaan 1200 mallinnushoitoon (urea kinetic modeling sessions),
joista oli käytettävissä hoitotiedot ja laboratoriokokeitten tulokset. Kehitettiin myös
menetelmä dialyysihoitomääräyksen laatimiseksi automaattisesti tietokoneen avulla
ja verrattiin eri tavalla laskettujen vakiopuhdistumien yhteyttä kuolleisuuteen.
Tulokset
1) Keinomunuaispotilaalla oman munuaistoiminnan osuus urean poistamisesta voi
olla jopa 40-50 %. Se alentaa pitoisuuksia ja suurentaa EKR- ja stdK-arvoja ja
voi korvata viikossa useita tunteja keinomunuaishoitoa. Vakiopuhdistuma on
käytännöllinen tapa ottaa huomioon jäljellä oleva munuaistoiminta, mikä keventää hoidosta aiheutuvaa taakkaa.
2) Hoitotiheyden lisääminen pidentämättä viikottaista hoitoaikaa laskee TAC- ja
PAC- ja nostaa EKR- ja stdK-arvoja. stdK on herkempi tiheydelle ja RRF:lle
kuin EKR.
3) Jos EKR pidetään vakiona, tiheyden lisääminen laskee PAC-arvoa. Jos stdK
pidetään vakiona, tiheyden lisääminen nostaa TAC-arvoa.
4) Tavanomaisessa 3 x 4 h/viikko hoitokaaviossa eKt/V-arvoa 1.2 vastaavat
EKR/V- ja stdK/V-lukemat olivat 3.44 ja 2.40 /viikko.
5) Keinomunuaishoidon annos voidaan sopeuttaa valkuaisen hajoamisnopeuteen
(PCR) rajoittamalla ureapitoisuuksia. Tietokoneella voidaan luoda automaattisesti hoitosuunnitelma, joka ottaa huomioon useita rajauksia ja tavoitteita. Vakiopuhdistumia tarvitaan, koska hoitotiheys saattaa muuttua.
12
Tiivistelmä
6) Tässä aineistossa EKR:lla oli merkitsevä yhteys kuolleisuuteen, sen sijaan
stdK:lla ei ollut. Valkuaisen hajoamisnopeus PCR ja dialyysiannos näyttävät liittyvän synergistisesti eloonjäämiseen.
7) Urean ja β2-mikroglobuliinin pitoisuudet reagoivat samalla tavalla hoitoajan ja
-tiheyden, mutta eri tavalla virtausnopeuksien muutoksiin. Ureapuhdistuma
riippuu voimakkaasti veren ja ulkonesteen virtauksesta, β2-mikroglobuliinin
puhdistuma vähemmän. Samalla urean vakiopuhdistumalla tai keskipitoisuudella
β2-mikroglobuliinin pitoisuudet ovat matalammat lempeämmässä hoidossa
(pienemmät virtaukset, pitempi hoitoaika).
Johtopäätökset
Yhtä ehdottomasti oikeaa keinomunuaishoidon annosmittaa ei ole. Urean kinetiikka on poikkeuksellista eikä kuvaa yleisesti ureemisten toksiinien käyttäytymistä.
Hoitotulokset tuskin paranevat urean poistamista tehostamalla.
Annos ja vaikutus on syytä erottaa toisistaan. Ureakineettiseen malliin perustuvat vakiopuhdistumat EKR and stdK ovat potilaasta riippuvia lukuja, jotka kuvaavat hoidon vaikutusta veren ureapitoisuuteen. Ne ottavat huomioon hoitotiheyden
ja jäljellä olevan munuaistoiminnan, mutta eivät sittenkään ole – pelkästään ureasta
laskettuina – ihanteellisia keinomunuaishoidon annosmittoja.
Keinomunuaishoidon annos voidaan määritellä viikottaisena urean dialysaattoripuhdistumana suhteutettuna ihon pinta-alaan (nKturea), esim 180 L/viikko/1.73
m2, mikä vastaa suunnilleen EKR-arvoa 14 mL/min, EKR/V-arvoa 3.6/viikko ja
stdK/V-arvoa 2.4/viikko tavanomaisessa 3 x 4 h/viikko hoitokaaviossa. Se takaa
helposti dialysoituvien aineitten riittävän puhdistuman, vaikka ei vastaa samansuuruista jatkuvaa puhdistumaa. Kt (puhdistuma x hoitoaika) voidaan mitata keinomunuaiskoneen lisälaitteen avulla. Ei tarvita verinäytteitä, ureakineettista mallia eikä
tietokoneita. Dialysaattoripuhdistuma ja hoitoaika määrittelevät annetun annoksen
ja heijastavat voimavarojen kulutusta. ECC, Kt/V ja URR ovat epäsuoria mittoja.
Tulevat tutkimukset, joissa annos (viikon nKt) on vakioitu, toivottavasti paljastavat parhaat keinot (aika, tiheys vai konvektio) ureemisten toksiinien hitaitten haittavaikutusten vähentämiseen. Annostelua ei voi kuvata yhdellä luvulla, tarvitaan
ainakin neljä: viikon nKt, konvektiovolyymi, kesto ja tiheys. Annos, annostelu,
riittävyys ja laatu ovat eri asioita.
Tiivistelmä
13
14
LIST OF ORIGINAL COMMUNICATIONS
LIST OF ORIGINAL COMMUNICATIONS
I FREQUENCY
Vartia A. Effect of treatment frequency on haemodialysis dose: comparison of
EKR and stdKt/V. Nephrol Dial Transplant 2009; 24:2797-2803.
II INCREMENTAL
Vartia A. Equivalent continuous clearances EKR and stdK in incremental
haemodialysis. Nephrol Dial Transplant 2012; 27:777-784.
III EQUIVALENCY
Vartia A. Urea concentration and haemodialysis dose. ISRN Nephrology 2013;
http://dx.doi.org/10.5402/2013/341026, accessed Nov 12, 2015.
IV AUTOMATION
Vartia AJ. Adjusting hemodialysis dose for protein catabolic rate. Blood Purif 2014;
38:62-67.
V ADEQUACY
Vartia A, Huhtala H, Mustonen J. Association of continuous-equivalent urea
clearances with death risk in intermittent hemodialysis. Accepted for
publication in Advances in Nephrology
(http://www.hindawi.com/journals/an/, accessed April 2, 2016 ).
Reprinted with permission of the original publishers. The thesis also contains
previously unpublished data.
LIST OF ORIGINAL COMMUNICATIONS
15
ABBREVIATIONS AND DEFINITIONS
BSA
C
C0
Ct
Cu
CAPD
CKD
DDQ
DPI
E
EBPG
ECC
EKR
EKRc
EKR/V
eKt/V
ESRD
fr
FSR
G
HD
HDF
HF
IDM
K
KDOQI
Kd
K0A
Kr
Kt
Kt/V
LVH
NBW
16
body surface area
concentration in blood or plasma
concentration at the beginning of dialysis session
concentration at the end of dialysis session
concentration in urine
continuous ambulatory peritoneal dialysis
chronic kidney disease
direct dialysis quantification
dietary protein intake
excretion or removal rate
European Best Practice Guidelines
continuous-equivalent clearance, equivalent continuous clearance
equivalent renal clearance = G / TAC
EKR normalized with distribution volume (mL/min/40 L)
EKR scaled by V (= stdEKR, /week)
equilibrated Kt/V
end-stage renal disease, CKD stage 5
dialysis session frequency
fractional solute removal
generation rate
hemodialysis
hemodiafiltration
hemofiltration
ionic dialysance monitoring
clearance
Kidney Disease Outcomes Quality Initiative
dialyzer clearance
dialyzer mass area coefficient
renal clearance
Kd * td, “urea product” (L)
Kt scaled to distribution volume (Kd * td / Vt)
left ventricular hypertrophy
normal body weight = Vt / 0.58 (kg)
ABBREVIATIONS AND DEFINITIONS
nEKR
nEKRant
nKr
nKt
nstdK
nstdKant
nPCR
PAC
PCR
Qb
Qd
HRQOL
RCT
rFC
rFSR
rFSRR
RRF
spKt/V
spvvUKM
SRI
stdEKR
stdK
stdK/V
TAC
TBW
td
ti
UF
UKM
URR
V
V0
V1
Vant
Ve
Vi
Vt
Vu
EKR normalized with BSA (mL/min/1.73m2)
EKR normalized with BSA and Vant (mL/min/1.73m2)
Kr normalized with BSA (mL/min/1.73m2)
Kt normalized with BSA (L/1.73m2)
stdK normalized with BSA (mL/min/1.73m2)
stdK normalized with BSA and Vant (mL/min/1.73m2)
PCR scaled to NBW
average predialysis concentration, peak average concentration
protein catabolic rate
dialyzer blood flow
dialyzer dialysate flow
health-related quality of life
randomized clinical trial
renal fractional clearance Kr/V
renal fractional solute removal = Vu * Cu / (C0 * V0)
renal fractional solute removal rate = rFSR / (td + ti)
residual renal function
single pool Kt/V
single pool variable volume UKM
solute removal index
EKR scaled by V (= EKR/V, /week)
standard clearance E / PAC
stdK scaled by V (/week)
time-averaged concentration
anthropometric total body water (Watson) = Vant
dialysis time, duration
interval time
ultrafiltration volume (positive, if fluid is removed)
urea kinetic model
urea reduction ratio
distribution volume
predialysis V
single-pool V
= TBW
“extracellular” pool V
“intracellular” pool V
postdialysis V
dialysis cycle urine volume ≈ interdialysis urine volume
ABBREVIATIONS AND DEFINITIONS
17
1 INTRODUCTION
The success of dialysis in sustaining life shows that the short-term mortality
associated with renal failure is mainly due to accumulation of dialyzable toxic
substances, including water, normally excreted by the kidneys. However,
amelioration of immediately life-threatening disturbances is not enough. The goal
is satisfactory quality and length of life.
Mortality among hemodialysis patients is much higher than that among general
population, in USA 188 vs 8 /1000 years at risk in 2012 [US Renal Data System
2015, Centers for Disease Control and Prevention; National Center for Health
Statistics 2015]. Quality and length of life are poorer than in many malignant
diseases [McFarlane 2009] and threatened by the residual syndrome [Depner
2001b], inconvenience, shortcomings, and complications of the treatment and
persistence or progression of the disease which has destroyed the kidneys. It is
difficult to separate the long-term side effects from inadequacy of the treatment
[Depner 1991a]. Encephalopathy due to aluminium accumulation from dialysate
was a serious adverse effect of hemodialysis in the 1970's. The exposure of blood
to artificial surfaces may result in activation of harmful biologic pathways [Aucella
et al. 2013]. Are acceleration of atherosclerosis, left ventricular hypertrophy or
amyloidosis due to treatment or its deficiencies? The effectiveness of hemodialysis
in uremic toxin removal is far inferior to that of healthy kidneys, and tubular
secretion and metabolic functions cannot be replaced by dialysis even in theory.
Hemodialysis efficiency can be quantified by changes in blood solute
concentrations resulting from the therapy [Gotch 1975]. Urea has been used for
that purpose, but it is not a good representative of uremic toxins.
Dosing of dialysis is one of the factors affecting outcome, but “adequacy” is not
simply equal to Kt/Vurea, and no randomized clinical trial shows a significant causal
relationship between dialysis dose and survival [Oreopoulos 2002].
18
INTRODUCTION
Moving of solutes across the dialyzer membrane can be described by the
clearance concept:
E=K*C
(1a)
K=E/C
(1b)
C = E / K,
(1c)
where E = removal rate, K = clearance and C = concentration. Equation 1a states
that the removal rate of a solute is directly proportional to its concentration. The
slope is referred to as clearance. In metabolic equilibrium removal rate equals
generation rate (G), thus
G=K*C
(2a)
K=G/C
(2b)
C=G/K
(2c)
Concentration reflects the balance between generation rate and clearance.
Kt/V and other measures of a single dialysis session can be used in comparing
dialysis dosing only if the treatment frequency is equal. Nonconventional schedules
have become more popular in recent years, but reports correlating outcome with
dose are inconsistent. Continuous-equivalent measures EKR [Casino and Lopez
1996] and stdK [Gotch 1998, Gotch et al. 2000] – based on the definition of
clearance – take the treatment frequency and residual renal function (RRF) into
consideration and were intended for use in comparing dialysis doses in different
schedules and to continuous dialysis and renal function. In this thesis I describe the
main characteristics of these measures, report the equivalency of them to eKt/V in
conventional dialysis, use them for automating the dialysis prescription and finally
attempt to correlate mortality with them in a small patient population.
INTRODUCTION
19
2 REVIEW OF THE LITERATURE
2.1 Uremic syndrome
2.1.1 Water and sodium
When 269 chronic hemodialysis patients were divided into two groups according to
predialysis water overload (above or below 15% of extracellular water) measured
by bioimpedance, the mortality risk was twofold in the higher group [Wizemann et
al. 2009]. Dry weight is a moving target, which, however, is worth aiming at.
Overhydration is associated with hypertension, heart failure, LVH, and intradialysis
blood pressure drops due to excessive ultrafiltration rate [Scribner et al. 1960] and
with death. The Tassin group in France has the best treatment results in the world,
summarized by [Charra et al. 2003]. Twenty-year survival was 43% despite
conservative practice [Charra et al. 1992b]. These authorities postulate that it is
mainly due to sodium restriction and long dialysis time, which allows slow
ultrafiltration and achieving the real dry weight and normal blood pressure slowly,
during a period of months. They have no control group and no randomized clinical
trials. Patient selection may have affected the results: a decreasing number of
patients are able or willing to go on eight-hour dialysis.
With volume control and salt restriction in 19 incident HD patients, blood
pressure and left ventricular mass decreased more than with antihypertensive
medication, but RRF also decreased more rapidly [Gunal et al. 2004].
Blood pressure control and other outcome measures have also been proved
excellent in slow nocturnal (home) HD in uncontrolled studies [Pierratos 1999,
Walsh et al. 2005] and randomized trials [Culleton et al. 2007, Rocco et al. 2011].
Long treatment time usually means high dose. The real dry weight is difficult to
achieve with short treatment without very strict dietary salt and fluid restriction.
Water balance is an essential element in renal replacement therapy and an art
form all of its own, but is addressed in the present thesis only in connection with
treatment time.
20
REVIEW OF THE LITERATURE
2.1.2 Acidosis
End-stage renal disease is commonly accompanied by metabolic acidosis [Teehan
et al. 1983]. Acidosis is a strong catabolic factor [Bergstrom 1995]. It can be
corrected efficiently by adjusting dialysate bicarbonate concentration. In the first
decades of hemodialysis history, acetate was used instead of bicarbonate for
technical reasons, but it had some degree of immediate toxicity. Lactate is better
tolerated and commonly used in CAPD and also in some special home
hemodialysis machines.
2.1.3 Anemia and endocrine disturbances
The most obvious cause of anemia in CKD is impaired production of
erythropoietin by the sick kidneys. Disturbances of renin, parathyroid hormone,
vitamin D and sex hormone metabolism are common in uremia, but can be
corrected only minimally by modifying the dialysis dose. They are not addressed in
this thesis.
2.1.4 Urea
Adding urea (CH4N2O, molecular weight 60 Da) to dialysate in uremic
concentrations caused only mild harmful short-term effects [Johnson et al. 1972,
Merrill et al. 1953]. In the NCDS trial the outcome was worse in the high TACurea
groups [Laird et al. 1983].
Urea concentration reflects the balance between generation and clearance, both
of which have a positive correlation with survival [Ravel et al. 2013]. In contrast to
the NCDS, in some studies – where DPI, PCR and Kt/V were not fully controlled
– higher urea concentrations were associated with better outcome [Shapiro et al.
1983]. In observational studies the correlation of mortality with predialysis urea
concentration is J- or U-shaped [Lowrie and Lew 1990, Stosovic et al. 2009]. With
equal clearance, urea concentrations are high if nPCR is high. High mortality
associated with low urea concentration [Degoulet et al. 1982] may be due to
malnutrition and wasting caused by comorbidity, and that associated with high
concentrations, to underdialysis.
REVIEW OF THE LITERATURE
21
2.1.5 Uremic toxins
Over 140 compounds which accumulate in renal failure and have harmful effects
have been identified [Duranton et al. 2012, Glorieux and Tattersall 2015, Glorieux
and Vanholder 2011, Lisowska-Myjak 2014, Neirynck et al. 2013b]. Uremic toxins
have different generation rates and removal kinetics, some are “middle” or big
molecules (500-40,000 Da) and dialyze poorly, some are bound to plasma proteins
or tissues and have peculiar dialysis kinetics despite their small molecular weight
[Dobre et al. 2013, Eloot et al. 2009, Glorieux and Vanholder 2011, Henderson et
al. 2001, Neirynck et al. 2013a]. Some uremic toxins are almost nondialyzable, but
are adsorbed to specific membranes [Piroddi et al. 2013]. Uremic toxins are usually
classified according to their dialyzability (Table 1, modified from [Glorieux and
Tattersall 2015], Creative Commons Attribution Non-Commercial License and
with permission of the publishers of Kidney Int and J Am Soc Nephrol).
Table 1. Key uremic retention solutes
Uremic
retention
solutes
MW
(Da)
Normal
concentration
mean
SD
Uremic
concentration
mean
SD
Small water-soluble
Urea (g/L)
ADMA (µg/L)
SDMA (µg/L)
60
202
202
<0.4
<60.6
76.1
2.3
878.7
646.4
1.1
38.4
606.0
5.7
14.5
8.5
11,818
24,500
26,000
1.9
4.0
7.0
1.6
43.1
8.6
57.8
18.0
3.7
10.8
22.7
2.1
8.2
188
212
175
179
195
1.9
0.5
0.5
3.0
NA
1.3
0.3
0.3
2.0
41.0
44.5
2.4
87.2
18.3
13.3
15.3
2.2
61.7
6.6
21.6
84.0
4.8
29.1
–
Middle molecules
β2m (mg/L)
IL-6 (ng/L)
TNF-α (ng/L)
Protein-bound
pCS (mg/L)
IS (mg/L)
IAA (mg/L)
HA (mg/L)
p-OHHA (mg/L)
21.0
Ratio
U/N
NA, not available; ADMA, asymmetric dimethylarginine; SDMA, symmetric dimethylarginine; β2m,
beta2-microblobulin; IL-6, interleukin-6; TNF-α, tumour necrosis factor-alpha; pCS, para-cresyl sulfate;
IS, indoxyl sulfate; IAA, indole acetic acid; HA hippuric acid; p-OHHA, para-hydroxyhippuric acid.
22
REVIEW OF THE LITERATURE
Water and potassium in excess may kill rapidly. Poorly dialyzed uremic
retention solutes, e.g. β2-microglobulin, kill slowly [Cheung et al. 2006, Davenport
2011, Depner 1991a]. Kinetics of potassium resembles that of urea [Vanholder et
al. 1992]. Phosphate behaves differently [Debowska et al. 2015]. We know
something about the correlation of specific uremic toxins with morbidity and
mortality, summarized by [Dobre et al. 2013, Liabeuf et al. 2014 and Neirynck et al.
2013b], but have no effective means to eliminate most of them separately – which
is not necessary given that uremia is not caused by retention of a few substances,
but is rather a disturbance of the biochemical milieu, homeostasis, interaction of
subtoxic concentrations of many substances [Depner 2001b]. Thus, unspecific
removal is an acceptable strategy [Baurmeister et al. 2009].
Concentrations of some uremic toxins correlate with PCR [Eloot et al. 2013],
but – paradoxically – dialysis patients with high PCR fare better than those with
low PCR [Ravel et al. 2013].
Clearance by diffusion is important in the removal of small molecules, such as
urea and potassium. Convection has only a small added value in removing these,
but plays a major role in the removal of larger uremic toxins. Increasing convection
expedites their removal relatively more than removal of urea [Daugirdas 2015].
Although many uremic toxins behave differently from urea [Eloot et al. 2005,
Eloot et al. 2007], increasing dialysis dose measured by urea clearance usually
enhances their removal and lowers their concentrations [Depner 1991b, Depner
1991c, Depner 2001b, Glorieux and Vanholder 2011, Gotch 1980, Neirynck et al.
2013a], but not in proportion to urea [Meyer et al. 2011, Sirich et al. 2012].
Increasing the session dose inevitably exacerbates technical problems, fluctuation
of volumes and concentrations and disequilibrium between body compartments
limiting this approach [Schneditz and Daugirdas 2001]. The intracorporeal rather
than extracorporeal solute transport may be a major limiting factor in the removal
of some uremic toxins [Eloot et al. 2014]. Increasing time and convection and
preservation of RRF are the main means to increase middle molecule removal.
β2-microglobulin (molecular weight 11,818 Da) is a marker of middle
molecules, but its dialysis kinetics is not as straightforward as that of urea and may
differ from other middle molecules [Vanholder et al. 2008].
Blood purification is not the only means to control the concentrations of
uremic toxins [Glorieux and Tattersall 2015]. Several protein-bound uremic toxins
are produced by degradation of amino acids by colonic bacteria [Lisowska-Myjak
2014, Neirynck et al. 2013a]. One approach to decrease uremic toxicity is by
REVIEW OF THE LITERATURE
23
absorbing from the gut and by affecting the intestinal flora [Liabeuf et al. 2014,
Schulman et al. 2006, Ueda et al. 2008]. In kidneys many uremic toxins are excreted
by specific tubular mechanisms in addition to glomerular filtration. RRF is
important in their removal [Marquez et al. 2011].
2.1.6 Causes of death
Cardiovascular events (40%) and infections (10%) are the most common causes of
death of hemodialysis patients [US Renal Data System 2015]. Water retention,
hypertension, left ventricular hypertrophy and hyperkalemia are obvious
mechanisms related to dialysis dosing, but the association may be more complex,
involving a chronic inflammatory state and several retention solutes. Blood access
is a remarkable source of infections.
2.2 Blood purification techniques
Only extracorporeal techniques circulating blood through an external device are
addressed. They include diffusion, convection, adsorption, and ion exchange, used
separately or concomitantly.
2.2.1 Diffusion and convection
In hemodialysis, blood and dialysate flow on opposite sides of a semipermeable
membrane. Solutes are driven through the membrane by concentration gradient
(diffusion) and by pressure gradient with the solvent drag (convection). The
contribution of convection to urea clearance is about 5% in low-flux hemodialysis
[Depner 1991a]. Large molecules are removed better by convection than by pure
diffusion [Eloot et al. 2014]. The glomeruli function by convection.
In hemofiltration (HF), all solute removal takes place by convection; no
dialysate is used, but replacement fluid is needed to achieve sufficient filtrate flow.
One randomized controlled trial shows better outcome, including survival, with
HF than with low-flux HD [Santoro et al. 2008].
In hemodiafiltration (HDF) both replacement fluid and dialysate are used. Some
internal hemodiafiltration without separate replacement fluid may take place in
24
REVIEW OF THE LITERATURE
high-flux dialyzers, when dialysate flows into blood in the dialysate inlet end
(backfiltration) and out at the other end.
2.2.2 Adsorption and ion exchange
Some solutes are adsorbed to the dialysis membrane in conventional dialysis
[Aucella et al. 2013, Eloot et al. 2014, Piroddi et al. 2013]. Hemoperfusion is a
technique based solely on adsorption; no extra fluid is used. Adsorption has been
utilized in intoxications, in replacing hepatic function and in regenerating the
dialysate [Ash 2009]. The low-flux membranes do not permeate β2-microglobulin
at all [Eloot et al. 2014]. With polysulfone membranes the majority of β2microglobulin removal occurs by diffusion and convection, with PMMA
membranes by adsorption [Aucella et al. 2013]. Adsorption and ion exchange
techniques alone do not suffice to sustain life in ESRD, but attempts have been
made to combine them with hemodialysis [Aucella et al. 2013].
2.3 Hemodialysis prescription
2.3.1 Dialysate composition and temperature
The concentrations of components of the dialysate, e.g. sodium, chloride,
bicarbonate, and calcium, are an essential part of the prescription, but do not affect
the removal of uremic toxins. Temperature likewise has nothing to do with the
dose, but lowering it may improve the hemodynamic stability. The positive effects
of HDF have sometimes been explained by that mechanism [Daugirdas 2015].
2.3.2 Filter and convection technique
Selection of the dialyzer determines the filtering characteristics and maximum
instantaneous clearance (mass transfer area coefficient K0A). Many modern
dialyzers combine biocompatibility, high efficiency (high K0A), high flux (high
permeability to water), and large pore size (high permeability to large molecules
permitting high clearance, especially with enhanced convection techniques). HDF
combines high clearance of small molecules by diffusion and high clearance of big
REVIEW OF THE LITERATURE
25
molecules by convection. There are also differences in the adsorptive capacity of
the membranes [Aucella et al. 2013, Perego 2013].
In the HEMO trial [Eknoyan et al. 2002], high flux correlated with better
outcome in patients with long dialysis history, with probably negligible RRF. Later
observational studies ([Canaud et al. 2006a, Canaud et al. 2015, Davenport et al.
2015]) and RCTs ([Santoro et al. 2008, Schiffl 2007], MPO [Locatelli et al. 2009],
CONTRAST [Grooteman et al. 2012], Turkish [Ok et al. 2013] and ESHOL
[Maduell et al. 2013a]) have also reported positive effects of convection. In MPO,
only patients with S-Alb < 40 g/L benefited significantly from high-flux dialysis
[Locatelli et al. 2009]. Mortality reduction was significant only in high-volume HDF
(filtration >23 L, ESHOL trial) and HF, but not in high-flux HD and low-volume
HDF. In high-flux HD, the convective transport is <10 L/session [Mostovaya et
al. 2014].
In one heavily criticized meta-analysis [Rabindranath et al. 2005] survival was
better with HD than with HDF. In one of the recent four meta-analyses HDF was
significantly better [Mostovaya et al. 2014], in three the benefit remained unproven
[Nistor et al. 2014, Susantitaphong et al. 2013, Wang et al. 2014]. [Locatelli et al.
2015] interpret these results as inconclusive. [Mostovaya et al. 2015] come to a
different conclusion. In their opinion, high-volume (>20 L) online post-dilution
HDF is an effective therapy and the convection volume is the most practical
measure of the dose of HDF. EBPG have recently been updated to favor high-flux
membranes [Tattersall et al. 2010], but probably their use is beneficial only in highvolume HDF. Obviously the added value of increased convection is rather small
because it has been so difficult to demonstrate.
2.3.3 Blood, dialysate, and filtrate flow
Michaels’ equation [Daugirdas and Van Stone 2001, Ward et al. 2011] (36 on page
93) describes the dependence of dialyzer diffusive clearance (Kd) on blood and
dialysate flow (Qb and Qd) and dialyzer K0A. With low permeability (low K0A,
middle molecules) the effect of flows on clearance is small. Convective transport
does not depend on dialysate flow. In RCTs a significant reduction in mortality has
been achieved by HDF only with high filtration volumes (>23 L/session) [Maduell
et al. 2013a]. Dialysate and replacement fluid cost, blood is free, but the access may
restrict its flow. For optimal urea removal blood and dialysate flows should be in
balance (1:1.5-2). In lengthy treatment sessions lower flows may be sufficient, but
26
REVIEW OF THE LITERATURE
dialysate consumption is still substantial. With modern dialyzers the effect of Qd
on Kdurea may differ from that calculated by Michaels’ equation [Hauk et al. 2000,
Leypoldt et al. 1997, Ward et al. 2011]. Ultrapure water is a prerequisite for
convective techniques. In post-dilution HDF, high filtrate flow also requires high
blood flow (Qb).
2.3.4 Duration and frequency
Treatment duration, frequency, and symmetry of the schedule are essential
elements of the prescription and have a decisive effect on solute removal, survival,
and HRQOL (sections 2.6.2 and 2.6.3). The interval between treatments is also
important. The odd number of days in a week causes difficulties for hemodialysis
patients in the conventional 3 x/week schedule. Mortality is highest on Mondays
and Tuesdays [Bleyer et al. 1999, Foley et al. 2011, Fotheringham et al. 2015].
Splitting the weekly treatment time into smaller fractions corrects this problem and
lowers concentrations, but may increase blood access complications [Jun et al.
2013, The FHN Trial Group 2010, Weinhandl et al. 2015].
2.3.5 Water removal
Fluid accumulation is a common problem in dialysis patients. Technically its
removal is simple, but the patients do not always tolerate it. Antihypertensive
medication may exacerbate blood pressure drops during dialysis and hamper
ultrafiltration leading to volume load, blood pressure rise, and a vicious circle.
Water removal is not addressed in this thesis.
2.3.6 Prescribed and delivered dose
Dialyzer clearance multiplied by treatment time (Kt) is based on dialyzer
characteristics, Qb, Qd, and td. It is a patient-independent, external measure of
delivered dialysis dose and often scaled to patient urea distribution volume V
(Kt/V). Traditionally the delivered dose has been estimated from its effects on the
patient’s blood urea concentrations because measurement of true Kd was difficult
before the advent of ionic dialysance monitoring (IDM) devices. Modeled Kt/V is
REVIEW OF THE LITERATURE
27
insensitive to errors of Kd, but V is not an ideal scaling factor (sections 2.6.4, 6.1
and 6.3).
In the USA the single pool Kt/Vurea is the primary measure of dialysis dose
[National Kidney Foundation 2015], obviously because it can be easily prescribed.
Even some observational registry studies are based on the prescribed dose
reflecting the intention-to-treat concept.
The KDOQI guidelines recommend a higher prescribed target Kt/V (1.4) to
guarantee a minimum delivered Kt/V (1.2) for all [National Kidney Foundation
2015]. In Europe, Qb, Qd, and td are often corrected arbitrarily if the delivered
dose target has not been achieved. The resulting new prescribed Kt/V is ignored
and forgotten and the focus is in the delivered dose.
If the Kt/V target is A (e.g. 1.2), then the required dialyzer clearance is
K=A*V/t
(3)
and the required treatment time
t = A * V / K,
(4)
where K is dialyzer clearance in mL/min, V is in mL and t in min.
V can be estimated from anthropometric equations [Hume and Weyers 1971,
Watson et al. 1980] and K from Michaels’ equation or nomograms published by
the dialyzer manufacturer.
We can choose the dialyzer, set K, t, and Qd and determine the required Qb
from a nomogram. Or we can set Qb and Qd and calculate Kd from Michaels’
equation and td from Equation 4.
Online monitors based on ionic dialysance or UV light absorption help in
delivering exactly the prescribed dose.
Taking into consideration the compartment effects and prescribing the required
Qb, Qd, and td to achieve a continuous-equivalent clearance target is more
complex and among the topics addressed in Study IV.
28
REVIEW OF THE LITERATURE
2.4 Delivered dose
2.4.1 Marker solutes
In the first decades the dialysis dose was calculated by the square meter-hour
concept [Babb et al. 1971, Charra et al. 1992a, Shinaberger 2001]. Currently the
delivered dose is estimated from the patient using marker solutes. Removal rate is
not a measure of dialysis efficiency because in metabolic equilibrium it is equal to
generation rate regardless of the intensity of dialysis. Urea has exceptional dialysis
kinetics and is not a good representative of uremic toxins, but has several
advantages as a marker: it is the main metabolite of ingested protein – over 90% of
nitrogen is excreted as urea –, abundant, easy to measure, distributed evenly in
body water, permeates cell membranes without difficulty, is not bound to plasma
proteins, and dialyzes well [Depner 1991a]. Survival correlates with urea-based
dose measures (section 2.6.1).
Formerly vitamin B12 (mw 1,355 Da) was as a marker of “middle molecules”
[Vanholder et al. 1995]. This is not a uremic toxin, but the corresponding measure
“dialysis index” correlated with signs of uremic neuropathy [Babb et al. 1975, Babb
et al. 1977, Babb et al. 1981, Milutinovic et al. 1978]. Later, β2-microglobulin has
been used as a representative of middle molecules. It fits with the concept of the
square meter-hour hypothesis [Babb et al. 1971]. The original aim of the NCDS
trial was to ascertain whether it was more important to eliminate small or middlesized molecules [Lowrie et al. 1976]. Dialysis time was a representative of removal
of middle molecules. Outcome correlated with it, but the association was not
significant and the middle molecules were forgotten for decades.
In the HEMO trial two markers were used: urea and β2-microglobulin
[Eknoyan et al. 2002]. The importance of middle molecules and other poorly
dialyzable uremic toxins and controversy about the relative importance of small
and large molecules has once again arisen [Vanholder et al. 2008], in association
with dialysis frequency, duration, and membrane [Daugirdas 2015]. Kt/Vurea does
not describe the clearance of middle molecules. Their removal depends mainly on
convection and weekly treatment time. Practices and devices which yield good
middle molecule clearance usually also yield sufficient urea clearance, in the range
where the effect of urea clearance on outcome levels out and the differences are of
little significance.
REVIEW OF THE LITERATURE
29
2.4.2 Concentration and clearance
Clearance reflects the removal rate and concentration changes during the dialysis
cycle, but uremic toxicity is more dependent on concentration levels [Sargent and
Gotch 1975]. In the National Cooperative Dialysis Study (NCDS) patients with
high time-averaged urea concentrations (TAC) fared worse than those with low
ones [Laird et al. 1983, Lowrie and Sargent 1980, Lowrie et al. 1981, Sargent 1983].
However, in a reanalysis of the NCDS material [Gotch and Sargent 1985] the
clearance-based variable Kt/Vurea was a better measure of dialysis dose than urea
concentration, because
1)
2)
3)
4)
urea concentration also depends on its generation rate
Kt is a patient-independent measure of delivered dialysis dose
scaling by urea distribution volume (V) is based directly on urea kinetics
approximate Kt/V can be derived from only two blood urea concentration
values (Equation 6)
5) Kt/V correlates with outcome more closely than urea concentration (section
2.6.1.)
Urea clearance is a useful descriptor of the treatment method, but the severity
of uremia depends on concentrations of true uremic toxins. In determining dialysis
dosing we must separate the dose – expressed as dialyzer clearance and treatment
time – from its effect and accept that other factors, too, affect the outcome.
2.4.3 Single-pool UKM
The intermittency of conventional hemodialysis entails some special problems and
solutions for measuring the dialysis dose delivered at one session [Farrell and
Gotch 1977, Gotch et al. 1974, Sargent and Gotch 1980].
Urea removal ratio (URR) describes the effect of dialysis on the patient. It has
been used widely in large epidemiological studies. It ignores RRF and UF.
URR = (C0 - Ct) / C0.
(5)
Solute removal index (SRI) or fractional solute removal (FSR) is a more
sophisticated version of URR [Keshaviah 1995, Keshaviah and Star 1994, Verrina
et al. 1998]. It takes UF into account and is often used in direct dialysis
quantification (DDQ).
30
REVIEW OF THE LITERATURE
Equation
Kt/V = ln(C0 / Ct),
(6)
where ln is the natural logarithm and C0 and Ct the pre- and postdialysis
concentrations, is the simplest urea kinetic model [Lowrie and Teehan 1983],
derived by mathematical integration from the clearance definition. The
concentration Ct after dialysis time t is
Ct = C0 * e -Kt/V,
(7)
where e is the base of the natural logarithm. Kt/V is a descriptor of the effect of
dialysis on blood urea concentration, scaled automatically – but perhaps not
optimally – to patient size and derived from only two blood urea concentration
measurements. URR and the approximate Kt/V (Equation 6) are mathematically
linked:
Kt/V = ln(1 / (1 - URR)).
(8)
Equation 6 is valid if
1) removal of urea by dialysis obeys the clearance equation 1a (on page 19)
2) urea is not removed via other pathways during dialysis
3) urea is not generated during dialysis
4) the whole mass of urea is evenly distributed in only one compartment
5) the size of the compartment remains constant during dialysis.
None of these conditions is true. The classic single pool variable volume urea
kinetic model (spvvUKM) [Sargent and Gotch 1980] corrects the inaccuracy of
Equation 6 due to ultrafiltration, urea generation, and water accumulation and
removal during the dialysis cycle. It outputs Vt and G. The equations (33 and 34 on
page 92) must be solved iteratively, because Vt and G appear in both. Kt/V is
calculated from Vt and the input variables Kd and td. The calculated Vt and G
depend heavily on Kd. Error in Kd causes a nearly proportional error in Vt, but a
50% error in Kd causes only 2% error in Kt/V [Buur 1991]. Ionic dialysance from
IDM can be used as Kd in UKM.
Several simple equations have been proposed for estimating session dose [Prado
et al. 2005]. The best validated is Daugirdas’ “second generation” logarithmic
equation for spKt/V [Daugirdas 1993, Daugirdas 1995]:
REVIEW OF THE LITERATURE
31
Kt/V = -ln(Ct/C0 - 0.008 * T) + (4 - 3.5 * Ct/C0 ) * UF/W,
(9)
where T is treatment time (h), UF ultrafiltration volume (L) and W postdialysis
weight (Kg). Daugirdas’ Kt/V has no assumptions regarding Kd and V, but is
based on the logarithmic decrease of concentration during the dialysis session
(Equation 6), with corrections for UF and G. Kd is not needed as an input
parameter. Garred's logarithmic equation has been validated in a smaller
population [Garred et al. 1994a]. Both have good concordance with the classic
spvvUKM.
The single pool UKM ignores the compartment effect, which appears e.g. as the
disequilibrium syndrome and a rapid rise in blood urea concentration (rebound)
after termination of the dialysis session, when urea from the sequestered body
compartments flows into the blood [Depner 1992, Gabriel et al. 1994].
[Depner and Bhat 2004] present a variable weekly nKt/V, which emphasizes
the frequency:
weekly nKt/V = 0.92 * N * (1 – e -1.1 * spKt/V),
(10)
where N is the number of sessions per week and e the base of the natural
logarithm.
All the abovementioned methods are based on urea. Scribner and Oreopoulos
emphasize the importance of time and frequency by introducing the “hemodialysis
product” (HDP) as the measure of dose [Scribner and Oreopoulos 2002]:
HDP = td * fr 2.
(11)
It is totally patient-independent like Kt. Equations 10 or 11 have not become
popular.
2.4.4 Double-pool UKM
During a hemodialysis session blood and extracellular fluid in highly perfused
organs are cleared efficiently, but solutes may remain sequestered in other tissues
and intracellularly. Dialysis rapidly reduces the plasma concentrations of such
solutes but removes only a small fraction of the total body content. After
termination of the session the concentrations equilibrate. Whole-body clearance is
lower than dialyzer clearance. A serial two-compartment (double pool) model,
developed in the 1970s [Abbrecht and Prodany 1971, Canaud et al. 2000,
32
REVIEW OF THE LITERATURE
Dombeck et al. 1975, Frost and Kerr 1977], describes urea concentrations during a
dialysis cycle fairly accurately. It gives urea generation rate G and the “intracellular”
and “extracellular” pool distribution volumes, which are needed in simulations.
The compartments are functional rather than anatomical entities. The
“extracellular” pool is that being dialyzed (blood and interstitial space), the
“intracellular” pool the peripheral poorly perfused tissues.
Correct G and V are essential prerequisites in simulations. Renal urea clearance
must be included as an input variable in UKM to obtain correct G, which is needed
for calculating ECC and PCR. PCR reflects DPI, is an important prognostic factor
[Ravel et al. 2013] and has interesting relationships to dialysis dosing (section 6.4).
Both single-pool and double-pool UKM require as input variables two or three
blood urea concentration values, dialyzer clearance Kd, renal urea clearance Kr,
and the usual dialysis cycle data. Alternatively, one can input V and compute Kd.
The double-pool urea kinetic model can also be applied to other substances if
the required parameters (generation rate, distribution volumes, dialyzer clearance,
and intercompartment transfer coefficient) are known. β2-microglobulin removal
has been described with a triple pool model [Odell et al. 1991]. Quadruple-pool
models for phosphate have been presented [Spalding et al. 2002].
[Daugirdas et al. 2009] have published a downloadable double-pool UKM
program Solute-Solver with source code. It includes assumptions and
approximations regarding the compartment volumes and intercompartment
transfer coefficients and can as such be applied only for urea. The overt strength of
Solute-Solver is that it has been published – and used e.g. by [Ramirez et al. 2012].
Unfortunately it has not been updated since July 2010 and has problems with
newer browsers and operating systems.
Downloadable computer programs for double pool UKM:
[Walther et al. 2006]: http://www.stanford.edu/~twmeyer/, accessed November
12, 2015
[Daugirdas et al. 2009] Solute-Solver, accessed November 12, 2015:
http://www.ureakinetics.org/calculators/batch/solutesolver.html
The mathematical models have been criticized [Lowrie 1996, Roa and Prado
2004]. “This is indeed a powerful analytic technique, and allows the physician to
take emotional distance from the disturbing uncertainties of dialysis” [Barth 1989,
page 209]. “Dialysis cannot be dosed” [Meyer et al. 2011, title].
REVIEW OF THE LITERATURE
33
2.4.5 eKt/V
Special attention must be paid to post-dialysis blood sampling to control access
and cardiopulmonary recirculation and post-dialysis rebound [Daugirdas and
Schneditz 1995, Pedrini et al. 1988, Schneditz et al. 1992, Sherman and Kapoian
1997, Tattersall et al. 1993].
Immediate post-dialysis plasma urea concentration (taken preferably
immediately before terminating the treatment session) is used in computing
spKt/V. Due to the compartment effect it overestimates patient clearance
[Kaufman et al. 1995]. At 30 min. post-dialysis the rebound is over, but the effect
of urea generation on its plasma concentration is still negligible or can be
estimated. This is the equilibrated post-dialysis concentration.
Waiting 30 min. for an equilibrated blood sample is inconvenient for both
patient and personnel. The equilibrated post-dialysis urea concentration can be
estimated from the immediate post-dialysis sample [Tattersall et al. 1996, Smye et
al. 1992] or by taking the sample 30 min. before termination of the session
[Bhaskaran et al. 1997, Ing et al. 2000, Canaud et al. 1995, Canaud et al. 1997,
Pflederer et al. 1995]. Equilibrated Kt/V (eKt/V) can be estimated directly,
without estimating first the equilibrated post-dialysis concentration, from spKt/V
and td with the “rate equation” [Daugirdas 1995, Daugirdas and Schneditz 1994]:
eKt/V = spKt/V - a * spKt/V / T + b,
(12)
where a and b are constants depending on the blood access (0.60 and 0.03 for AV
and 0.46 and 0.02 for VV) and T is td in hours. The equation was further modified
for the HEMO trial [Daugirdas et al. 2004].
spKt/V overestimates dialysis efficiency especially in short high-efficiency
treatments, which in the USA led to underdialysis and high mortality in the 1980's
[Barth 1989, Berger and Lowrie 1991, Parker TF 1994, Roa and Prado 2004,
Shinaberger 2001, US Renal Data System 2015]. EBPG recommend eKt/V as the
primary dose measure. This makes the short and long sessions more
commensurable.
With spKt/V = 1.20, eKt/V calculated with Equation 12 (AV access) is:
34
td (h)
2.5
4.0
6.0
8.0
eKt/V
0.94
1.05
1.11
1.14
REVIEW OF THE LITERATURE
The eKt/V concept does not replace the true double pool UKM. It cannot be
used in simulations and in calculating V, G and PCR.
2.4.6 Direct dialysis quantification (DDQ)
The method is based on total or partial dialysate collection [Cappello et al. 1994,
Mactier et al. 1997, Malchesky et al. 1982]. It has been held as the gold standard in
urea measurement before the era of double-pool blood side kinetics and adsorptive
membranes, but is cumbersome and prone to measurement errors [Alloatti et al.
1993, Bankhead et al. 1995, Bosticardo et al. 1994, Buur 1995, Buur and Larsson
1991, Casino et al. 1992, Depner et al. 1996, Di Filippo et al. 1998b, Di Filippo et
al. 2004, Gabriel et al. 1994, Kloppenburg et al. 2004, Mactier et al. 1997,
Vanholder et al. 1989]. It takes the compartment effect into consideration and
requires the same kind of iterative computations as the classic UKM.
2.4.7 Online monitoring
With a urea monitor the urea concentration of effluent dialysate is measured at
short intervals, the double-pool constants determined with curve-fitting techniques,
and all essential double-pool UKM values computed during the dialysis session
[Bosticardo et al. 1994, Depner et al. 1996, Depner et al. 1999, Garred 1995,
Sternby 1998]. The method is accurate, but impractical and expensive.
Online ionic dialysance monitor (IDM; Fresenius OCM, Baxter Diascan)
increases the dialysate concentration momentarily, monitors the conductivity
change in the dialysate outlet, and calculates the ionic dialysance (conductivity
clearance), which is near to urea clearance [Di Filippo et al. 1998a, Di Filippo et al.
2001, Gotch 2002, Gotch et al. 2004, Lowrie et al. 2006, Manzoni et al. 1996,
Polaschegg 1993]. It can do this several times during every dialysis session at
almost no cost. IDM does not replace UKM but complements it by providing the
most problematic UKM input parameter Kd [Di Filippo et al. 2004, Wuepper et al.
2003]. Ionic dialysance corresponds to effective clearance, taking access and
cardiopulmonary recirculation into account but not the compartment effects.
Devices monitoring the concentrations of uremic retention solutes in the
effluent dialysate by UV light absorption have been developed for estimating
dialysis efficiency online – unfortunately using Kt/Vurea as the reference –
REVIEW OF THE LITERATURE
35
[Castellarnau et al. 2010, Donadio et al. 2014, Uhlin et al. 2003] and implemented
in dialysis machines (Braun Adimea). They estimate K/V from the logarithmic
absorbance versus time curve; K and V cannot be determined separately. Reports
on experiences with these are rarer than with ionic dialysance devices.
Guidelines recommend monthly checking of the delivered dose. With online
monitoring of ionic dialysance or UV absorption it can be done at every session.
2.4.8 Residual renal function
Creatinine clearance is commonly used as a measure of renal function in
nondialysis patients. It is higher than urea clearance, because urea is reabsorbed,
but creatinine is excreted in the tubules. EBPG 2007 recommend the average of
urea and creatinine clearance as the measure of RRF of dialysis patients [Tattersall
et al. 2007]. KDOQI recommends urea clearance [National Kidney Foundation
2015]. It conforms better to the practice of using urea kinetics in dialysis dosing
because one of the parameters in UKM is renal urea clearance. Expressing RRF as
urea clearance permits calculation of correct G and PCR and is a safe way to sum
RRF and dialysis. Continuous-equivalent measures derived from true UKM include
renal urea clearance automatically.
Renal clearance can be assessed using radiolabeled solutes 51Cr-EDTA, 99mTcDTPA or 125I-iothalamate [Krediet 2006], but the guidelines [National Kidney
Foundation 2015, Tattersall et al. 2007] recommend calculation from urine
collection and the average of corresponding post- and predialysis urea
concentrations. The concentration profile during the interval is curvilinear,
flattening out towards the end of the period. Thus the average concentration
(denominator) calculated this way is lower than the time-averaged value, and renal
urea clearance is overestimated. [Gotch and Keen 1991] have presented formulae
emphasizing the higher predialysis concentration:
Kr = Vu * Cu / (t * (0.25 * Ct1 + 0.75 * C02)
(3 x/week)
(13)
Kr = Vu * Cu / (t * (0.16 * Ct1 + 0.84 * C02)
(2 x/week),
(14)
where Kr = renal urea clearance, Vu = collected urine volume, Cu = urine urea
concentration, Ct1 = postdialysis plasma urea concentration of the preceding
dialysis session and C02 = predialysis plasma urea concentration at the end of urine
36
REVIEW OF THE LITERATURE
collection. Gotch and Keen recommend collecting urine for only 24 h before
dialysis. They also describe a formula for “adding” RRF to dialysis session Kt/V:
Kt/Vadj = K t/V + b * Kr / V,
(15)
where Kr is renal urea clearance in mL/min, V is in mL and b is 4,500 in 3 x/week
schedule and 9,500 in 2 x/week.
2.5 Continuous-equivalent clearance (ECC)
2.5.1 Aiming at a universal dose measure
Dialyzer urea clearance may be several times greater than that of healthy kidneys,
but conventionally it is in effect only during less than ten percent of the time. The
fluid shifts and concentration fluctuations restrict the usefulness of intermittent
hemodialysis.
Kt/V and other measures of a single dialysis session can be used in comparing
dialysis dosing only if the treatment frequency is equal [Depner 2001a]. Clearance
K (Kd) and duration t (td) have equal weight in Kt and Kt/V: four hours with K =
200 mL/min is equal to two hours with K = 400 mL/min, but Kd and td may not
have the same impact on solute removal, due at least in part to the compartment
effects [Basile et al. 2011, David et al. 1998, Eloot et al. 2008]. Prescribed weekly
Kt/V is equal whether the patient is dialyzed six hours two times per week or two
hours six times with equal dialyzer clearance, but solute concentrations and
treatment outcomes are not equal.
The promising outcomes achieved recently with frequent HD accentuate the
need of a universal dose measure in investigating the relationship between dose
and outcome. It is not clear whether these are due to higher clearance or lesser
fluctuation in volumes and concentrations or other factors. In most investigations
the weekly dose has been higher in the frequent group or it has not been
appropriately reported.
2.5.2 Definitions based on UKM
EKR (ECCTA) and stdK (ECCPA) are based on the definition of clearance:
REVIEW OF THE LITERATURE
37
K=E/C
(1b on page 19)
In steady state the removal rate E equals the generation rate G, thus
K=G/C
(2b on page 19)
Urea concentrations fluctuate in intermittent dialysis. If C is the time-averaged
concentration (TAC) during the dialysis cycle, then the equation can be said to
describe the average clearance (dialysis + RRF), if G is constant [Depner 1991a]
and equal to removal rate E. Casino and Lopez named this expression equivalent
renal clearance (EKR, time-average clearance) [Casino 1999, Casino and Lopez
1996]:
EKR = G / TAC
(16)
In conventional intermittent hemodialysis EKR is typically 12-15 mL/min or
120-150 L/week, significantly higher than in CAPD or the renal clearance in
ESRD patients without dialysis. The inferior efficiency of hemodialysis may be due
to the intermittency, including compartment disequilibrium or differences in the
solute transport profile of kidneys, peritoneum, and dialyzer membrane or other
factors. Gotch tried to resolve the discrepancy by implementing the stdK concept
[Gotch 1998, Gotch 1999, Gotch et al. 2000], based on the “peak concentration
hypothesis”, which assumes that high concentration peaks are especially harmful
[Clark and Ronco 2001, Keshaviah et al. 1989]. With comparable outcomes the
weekly average peak concentration (PAC) in conventional hemodialysis and the
constant concentration in CAPD are about equal.
stdK = G / PAC
(17)
The unit of EKR and stdK is e.g. mL/min or L/week. Both may be scaled to
body size by dividing by urea distribution volume V and expressed as EKR/V and
stdK/V:
EKR/V = EKR / V
(18)
stdK/V = stdK / V.
(19)
The most practical unit of EKR/V and stdK/V is /week. G, V, TAC and PAC
can be determined by kinetic modeling. Because Kr is an input variable in
computing G by UKM, these variables are not pure dialysis measures but also
include RRF.
EKR/V and stdK/V are equivalent continuous clearances scaled by distribution
volume V. Unfortunately expressions with operators are used as variable names,
38
REVIEW OF THE LITERATURE
such as Kt/V, EKR/V and stdK/V. This may cause confusion in equations like
18, 19 and 29. In Studies I-IV of the present thesis EKR/V is called stdEKR.
stdKt/V is a dimensionless misnomer, not an ECC. In Studies II-V stdK/V is
used instead of stdKt/V. With equal treatment stdK < EKR.
For full conformity with the peak concentration hypothesis, the predialysis
concentration after the longest interval should be substituted for C in Equation 2b
on page 19. EBPG 2007 recommend this approach and call the variable SRI
[Keshaviah 1995, Tattersall et al. 2007], but it is poorly documented and has not
been used in outcome studies. Of course, the actual peak concentration is simpler
to determine than PAC or TAC.
The peak concentration hypothesis has not been confirmed empirically. In the
old NCDS trial TAC correlated more closely with outcome than PAC [Laird et al.
1983]. The stdK/V concept may be an artificial attempt to render continuous and
intermittent therapies commensurable. According to Daugirdas, stdK/V is not a
true continuous urea clearance, but a clearance “compressed” by about 1/3 and is
extremely sensitive to dialysis frequency. It may also reflect the impact of
sequestered small molecular weight solutes [Daugirdas 2014]. There are no studies
demonstrating which is more closely associated with outcome, EKR/V or stdK/V.
EKR/V is more sensitive to schedule asymmetry than stdK/V [Daugirdas and
Tattersall 2010]. Schedule asymmetry is not addressed in the present thesis.
Comprehensive analyses concerning the relationships between EKR, stdK and SRI
have been presented by [Waniewski et al. 2006, 2010] and [Debowska et al. 2011].
2.5.3 Simple equations
Ideally G, V, TAC, and PAC in the above equations should be from double-pool
UKM for greater accuracy, especially in simulations. Gotch and Leypoldt have
developed equations for estimating stdK/V without UKM [Gotch 2004, Leypoldt
2004, Leypoldt et al. 2004]. They do not take RRF and convection into
consideration, but are pure diffusive dialysis measures [Diaz-Buxo and Loredo
2006a, Diaz-Buxo and Loredo 2006b]. [Daugirdas et al. 2010a] have proposed a
complex calculation method involving fluid removal and residual kidney clearance.
Weekly URR is an approximation of stdK/V. FSR, SRI and URR are “kinetically”
additive, Kt/V is not [Waniewski and Lindholm 2004].
REVIEW OF THE LITERATURE
39
2.5.4 Guidelines
The KDOQI guidelines for hemodialysis adequacy have recently been updated to
take RRF and UF into consideration in stdK/V and recommend 2.3/week as the
target for schedules other than thrice weekly [National Kidney Foundation 2015].
The EBPG 2002 guidelines recommended 13 - 15 mL/min as the minimum
adequate EKR if the patient has significant RRF [Kessler et al. 2002], but the 2007
version includes no recommendations for EKR [Tattersall et al. 2007]. Instead, a
solute removal index SRI of 2.0/week is recommended as a minimum for patients
with RRF or with other than a 3 x/week schedule.
2.6 Dependence of outcome on dose (adequacy)
2.6.1 Session dose
Abundant information on the association of better outcome with higher dose in
conventional 3 x/week schedule is available from large observational studies before
HEMO (>10,000 patients: [Li et al. 2000, Lowrie et al. 2002, Owen et al. 1993,
Owen et al. 1998, Port et al. 2002, Shinzato et al. 1996, Shinzato et al. 1997]). Most
studies on the association of outcome with dialysis dose are based on urea
clearance. In some studies no correlation between Kt/V or URR and survival was
found [Bleyer et al. 1996, Charra 2001, Charra et al. 1992a, Combe et al. 2001,
Panaput et al. 2014, Salahudeen et al. 2003]. The mortality curve levels out or is Jshaped, probably due to malnutrition in the high dose groups [Chertow et al. 1999,
Miller et al. 2010]. In some cross-sectional studies the correlation of Kt with
survival was stronger than that of Kt/V [Li et al. 2000, Lowrie et al. 1999, Lowrie
et al. 2005].
No significant positive correlation between dose and survival was found in the
randomized controlled HEMO trial. However, in subgroup analyses the higher
dose resulted in better survival among women. HEMO may be confounded by the
“dose-targeting bias” [Greene et al. 2005]. It has been criticized for using V as the
scaling factor [Lowrie et al. 2005] and for improper extensions to more frequent
therapies [Roa and Prado 2004].
After HEMO only few reports on association between dose and survival have
been presented [Depner et al. 2004, Termorshuizen et al. 2004]. In a large material
40
REVIEW OF THE LITERATURE
(84,936 patients) high dialysis dose was associated with lower mortality among
women but not among men [Port et al. 2004].
There are no RCTs reporting an unequivocal cause and effect relationship
between dialysis dose and outcome [Oreopoulos 2002]. Some outcome studies are
summarized by [National Kidney Foundation 2006].
Some factors cause dissociation between dialysis adequacy and Kt/V
[Vanholder et al. 2002]. The most important are the large-pore membranes,
nonconventional schedules and changed patient population. The survival curve
levels out with increasing dose, but has shifted over the decades [Honkanen et al.
2014, Szczech et al. 2001]. The limits have been reached in the conventional incenter 3 x/week schedule. Dose measurement methods based on urea clearance are
not optimal.
2.6.2 Treatment duration
In the early studies urea concentration was adjusted to a constant level with UKM.
No difference in outcome was detected when the patients were divided into four
groups according to treatment duration [Gotch et al. 1976]. In the randomized
NCDS trial the positive effect of time was considerable, but not statistically
significant (P = 0.06) [Laird et al. 1983, Lowrie et al. 1981, Parker et al. 1983],
which led to shortening of treatments, especially in the USA [Gotch and Uehlinger
1991]. In Tassin the normal treatment duration was eight hours with excellent
survival [Charra et al. 2003]. The association between session length and survival is
strong in Japan, weaker in Europe and almost nonexistent in the USA in sessions
longer than 3.5 hours [Daugirdas 2014].
Removal of solutes with large distribution volume or low dialyzer clearance or
impaired inter-compartment mass transfer benefits more from time than urea
[David et al. 1998, Eloot et al. 2008, Glorieux and Vanholder 2011], review [Eloot
et al. 2012].
Increasing treatment duration is the simplest way to increase session Kt and
Kt/V. In many investigations the effect of time has not been separated from the
dose and environmental factors (institution or home, day or night) [Lacson et al.
2012, Nesrallah et al. 2012, Ok et al. 2011], reviews [Diaz-Buxo et al. 2013, Hakim
and Saha 2014, Walsh et al. 2005]. In some studies the material has been adjusted
for Kt/Vurea [Brunelli et al. 2010, Flythe et al. 2013, Lockridge and Kjellstrand
REVIEW OF THE LITERATURE
41
2011, Marshall et al. 2006, Miller et al. 2010, Saran et al. 2006, Shinzato and Nakai
1999, Shinzato et al. 1996, Shinzato et al. 1997] and an independent advantage of
longer duration confirmed. In a population of 262 short-daily hemodialysis patients
survival was associated with weekly treatment time and site but not with Kt/V or
stdK/V [Kjellstrand et al. 2010].
Several uncontrolled enthusiastic reports on long nocturnal HD in small patient
populations have appeared, but in the frequent long nocturnal arm of the
controlled FHN trial [Rocco et al. 2011] the outcome was not essentially better
than in conventional 3 x/week treatment and long-term mortality was even higher
[Jardine and Perkovic 2015, Rocco et al. 2015]. There were severe recruitment
difficulties in the FHN trial. Patients indifferent as to whether they will be
randomized to conventional in-center or frequent nocturnal home hemodialysis
form a small and special group and are not a representative sample of the dialysis
population as a whole. In a recent nonrandomized controlled study of 494 patients,
survival and many soft endpoints were significantly better with longer treatment
time [Ok et al. 2011].
Time has an essential role in ultrafiltration and fluid balance. Increased dialysis
time leads to better control of volume excess, to reduced occurrence of
intradialysis hypotension, and to better control of serum phosphorus [Daugirdas
2013].
Sometimes the patient demands that the session be curtailed [Sehgal et al. 1998]
or occasional interruptions are included in the treatment time (“the wall clock
syndrome” [Depner 1994]). Patients may be happy to extend their total time on
dialysis provided they feel better between treatments [Eloot et al. 2014, Honkanen
et al. 2014].
The role of treatment time has not been conclusively determined; investigation
continues (the TiME trial, https://clinicaltrials.gov/ct2/show/NCT02019225,
accessed November 12, 2015).
2.6.3 Treatment frequency
Deaths are more frequent on the day after the long interval [Bleyer et al. 1999,
Foley et al. 2011, Fotheringham et al. 2015]. The alternate-day schedule corrects
this drawback [Georgianos and Sarafidis 2015]. Excellent results have been
reported from eight-hour alternate day nocturnal home dialysis [Jun et al. 2013].
42
REVIEW OF THE LITERATURE
In a Chinese nonrandomized study survival was better in the 2 x/week group
than in the 3 x/week, also in a subgroup on dialysis for over five years [Lin et al.
2012]. In another Chinese study, quality of life scores did not differ between the
twice and thrice weekly groups [Bieber et al. 2014].
In several small observational studies with or without historical or registry
controls many advantages of high frequency have been reported. These include
blood pressure, LVH, phosphorus control, anemia, and HRQOL. On the other
hand, the frequency of blood access complications has commonly increased [Jun et
al. 2013, Weinhandl et al. 2015]. Some reviews criticize the observational studies on
frequent dialysis: the results are good, but the studies poor [Lacson and Diaz-Buxo
2001, Perl and Chan 2009, Suri et al. 2006, Walsh et al. 2005]. In one observational
study [Suri et al. 2013] outcomes of short daily in-center treatment were poorer
than in conventional treatment. An excellent review has been presented by [DiazBuxo et al. 2013].
In a small RCT (52 patients) [Culleton et al. 2007] frequent nocturnal
hemodialysis had positive effects on left ventricular mass, blood pressure, mineral
metabolism, and quality of life.
In the randomized controlled short daily FHN trial “frequent hemodialysis, as
compared with conventional hemodialysis, was associated with favorable results
with respect to the composite outcomes of death or change in left ventricular mass
and death or change in a physical-health composite score but prompted more
frequent interventions related to vascular access”, and “the net effects of frequent
hemodialysis will need to be balanced against the added burden for the patient and
societal cost” [The FHN Trial Group 2010, pages 2287 and 2299].
In the frequent nocturnal FHN trial patients had improved control of
hyperphosphatemia and hypertension, but no significant benefit in survival or left
ventricular mass [Rocco et al. 2011]. Long-term mortality was higher than in the
conventional group [Rocco et al. 2015]. A cohort study also suggests that 5-7
weekly sessions are associated with poorer survival [Suri et al. 2013].
Average weekly treatment time and stdK/V were in the frequent FHN groups
considerably higher than in the 3 x/week groups. Thus the effects of frequency,
duration, and dose cannot be differentiated.
No meta-analyses of the RCTs concerned on duration and frequency have been
presented. A comprehensive review is presented by [Eloot et al. 2014]. Another
recent review prefers conventional 3 x/week dialysis but with longer treatment
times than is currently recommended [Hakim and Saha 2014]. According to EBPG
REVIEW OF THE LITERATURE
43
2007 Guideline 1.1, dialysis should be delivered at least 3 x/week and the total
duration should be at least 12 h/week [Tattersall et al. 2007]. KDOQI 2015 does
not set absolute limits. Daugirdas' recent opinion is that 2 x/week may suffice if
the patient has considerable RRF [Daugirdas 2015]. stdK/V is affected by
frequency more than EKR/V.
Increasing frequency often means increasing weekly treatment time and enables
higher weekly dose, but stdK/V and EKR/V may be increased and concentrations
decreased also by increasing frequency with equal Kd and weekly td [Clark et al.
1997, Depner 1998, Galland et al. 1999, Goldfarb-Rumyantzev et al. 2002,
Leypoldt 2005].
2.6.4 Scaling
Dialyzer clearance K and treatment time t are input parameters in UKM. Only the
scaling factor V is computed by kinetic calculations. V is also an independent
prognostic factor: Physically large patients (with high V) have a survival advantage
in hemodialysis with equal Kt/V [Lowrie et al. 2004, Owen et al. 1998, Owen et al.
2001, Wolfe et al. 2000]. Obese persons likewise have a survival advantage despite
lower V/weight [Abbott et al. 2004, Port et al. 2002, Wolfe et al. 2000]. On the
other hand, high modeled V and its rise over time reflect overhydration and predict
poor outcome [Daugirdas et al. 2011]. Anthropometrically estimated total body
water is greater than modeled urea volume [Daugirdas et al. 2003].
Kt (urea product) is a patient-independent measure of dialysis session dose, and
recommended by [Chertow et al. 1997, Li et al. 2000, Lowrie et al. 1999, Lowrie et
al. 2002, and Maduell et al. 2013b]. Kt omits the compartment effects and other
patient-dependent tasks. Obviously scaling is needed. Outside dialysis, clearances
are commonly scaled to BSA. With equal Kt/V, women and small people have
poorer outcome and a smaller V/BSA ratio than men and large individuals
[Daugirdas et al. 2003, Daugirdas et al. 2010b, Depner et al. 2004, Hume and
Weyers 1971, Miller et al. 2010, Spalding et al. 2008]. [Greene et al. 2009] have
proposed a corrected V(n) = 3.271 * V2/3 to be used in stdK/V. Some
investigators have proposed adjusting Kt and stdK/V to BSA [Daugirdas 2014,
Daugirdas 2015, Daugirdas and Greene 2005, Daugirdas et al. 2008a, Daugirdas et
al. 2008b, Daugirdas et al. 2010c, Lowrie et al. 2005, Lowrie et al. 2006, Ramirez et
al. 2012]. This enhances the dose to women and children. Bioelectrical resistance
has also been presented as a scaling factor [Basile et al. 2010a, Basile et al. 2010b].
44
REVIEW OF THE LITERATURE
Which V – predialysis, postdialysis or time-averaged – should be used in the
continuous-equivalent clearance equations (18-19 on page 38) as the reference has
not been clearly defined. Postdialysis urea distribution volume (Vt) has been used
in the Solute-Solver program [Daugirdas et al. 2009] and in the present thesis.
2.6.5 Residual renal function
The renal excretion profile of uremic solutes is different from that of dialysis.
Renal function is “qualitatively” superior to dialysis with equal urea clearance
[Marquez et al. 2011, Suda et al. 2000, Vilar and Farrington 2011, Vilar et al. 2009].
RRF improves the outcome of dialysis patients [Chandna and Farrington 2004,
Depner 2005, Ng et al. 2007, Perl and Bargman 2009, Shafi et al. 2010, Shemin et
al. 2001, Termorshuizen et al. 2004], but early treatment with substantial RRF
[Clark et al. 2011, Hwang et al. 2010, Korevaar et al. 2002, Rosansky et al. 2011,
Sawhney et al. 2009, Stel et al. 2009, Wright et al. 2010; 896,546 patients] and
extreme attempts to preserve it by allowing overhydration are not beneficial
[Canaud et al. 2006b, Gunal et al. 2004, Ng et al. 2007, Van Stone 1995].
Renal urea clearance may justify marked reductions in dialysis dose [Daugirdas
2014]. There are no reports showing that full-dose dialysis for patients with RRF is
better than the incremental approach [Kalantar-Zadeh et al. 2014, Vilar et al. 2009].
In incident HD patients, mortality during the first six months is very high
[Kalantar-Zadeh et al. 2014].
In incremental dialysis RRF must be controlled regularly and the prescription
corrected if RRF decreases.
2.6.6 Continuous-equivalent clearance
If correctly calculated, ECC combines RRF and dialysis and makes different
treatment schedules commensurable. Few reports correlate outcome directly with
continuous-equivalent clearance.
[Barreneche et al. 1999] correlate mortality with EKR. Death risk was 2.17
when EKRc was below the median 14.2 mL/min/40 L.
[Manotham et al. 2006] studied EKRc in twice-weekly hemodialysis. Serum
albumin was used as the outcome measure. EKRc above 13 mL/min/40 L had
REVIEW OF THE LITERATURE
45
respectively 90% and 100% probabilities of maintaining monthly and 12-month
serum albumin levels above 40 g/L. For this, Kt/V should exceed 2.2.
In daily home HD of 191 patients, survival was independently associated with
stdK/V (HR 0.29, P<0.001). Survival was highest in the group where stdK/V
exceeded 5.1/week [Lockridge et al. 2012]. stdK/V was calculated with the
Leypoldt equation.
In the FHN short arm, total stdK/Vurea was significantly higher in the frequent
group than in the conventional group (3.60 vs. 2.57/week). Frequent hemodialysis
was associated with significant benefits [The FHN Trial Group 2010]. In the FHN
nocturnal arm the difference in stdK/V was even greater (5.03 vs. 2.91/week)
[Rocco et al. 2011]. No definitive benefit of more frequent nocturnal hemodialysis
could be demonstrated.
It is not possible to deduce the significance of higher stdK/V in the FHN trials.
“Alternatively, the benefit of frequent hemodialysis in the short daily arm may
result from improved control of other metabolic by-products, such as phosphate
or other retained uremic solutes, more physiologic removal of solutes (yielding
lower and less variable time-averaged solute concentrations), or improved control
of extracellular volume excess (reducing the time-averaged fluid load)” [The FHN
Trial Group 2010, page 2295].
2.6.7 Overdialysis
Increasing dialysis intensity without clear benefits is overdialysis, but the limit has
been difficult to determine. According to [Gotch et al. 1997] it is spKt/V 1.1 and
according to HEMO spKt/V 1.32 or eKt/V 1.16 in the 3 x/week schedule, but
several studies report clear benefits from higher doses, at least in selected cases
[Szczech et al. 2001]. In the cohort of [Salahudeen et al. 2003] the mortality in the
highest Kt/V quintile (>1.68) was higher than in the lower quintile. These authors
suspect that efficient dialysis would be harmful for sick and malnourished patients.
The frequent nocturnal hemodialysis with slightly reduced flows (Qb 262±62, Qd
354±106 mL/min) and total weekly stdK/Vurea 5.03±1.23/week may be an
example of overdialysis with higher long-term mortality than in conventional
treatment [Rocco et al. 2015]. In high frequency schedules access complications are
more common [Jun et al. 2013, Weinhandl et al. 2015].
46
REVIEW OF THE LITERATURE
Phosphate depletion has been observed in nocturnal HD. Some other nutrients,
e.g. amino acids and vitamins may also be dialyzed out of the patient and need to
be replaced [Dobre et al. 2013, Hawley et al. 2008].
Several possible threats or complications of intensive HD have been presented:
increased risk of blood access events, accelerated loss of residual function,
intravascular volume depletion resulting in organ hypoperfusion, burnout in home
HD and exposure to harmful substances and surfaces present in the dialyzer circuit
which may cause platelet activation and microbubbles [Daugirdas 2014, Rocco et
al. 2015]. The quality-adjusted life years and their unit costs must also be
considered. Health care resources need to be prioritized for interventions of
proven efficacy.
2.6.8 Soft endpoints
Significant improvements in soft endpoints have been reported in many RCTs
where the effect of the dosing intervention on survival has been positive, but not
statistically significant. These include blood pressure, intradialytic hypotension,
LVH, hospitalization, nutritional status, and several laboratory values. Few reports
associate HRQOL with dialysis dose [Hornberger 1993]. Most experiences concern
on frequent dialysis [Mohr et al. 2001, Williams et al. 2004]. The treatment
environment (home or center) and timing (day or night) are not essential factors in
dosing, but may affect acceptance, compliance, survival and HRQOL.
REVIEW OF THE LITERATURE
47
48
AIMS OF THE STUDY
3 AIMS OF THE STUDY
The purpose of this thesis was to search for answers to following questions:
3.1 Is high mortality in hemodialysis due to low dose?
Mortality among hemodialysis patients is unacceptably high. Reviewing the
literature revealed too low dialysis dose as one possible explanation. Is the
association between dose and mortality valid in our patient population?
3.2 How should the dialysis dose be measured?
Doses must be measured before they can be convincingly compared and
increased. Session doses cannot be used as uniform measures in different
schedules. Several reports describe favorable results from long or frequent
hemodialysis, but it is not clear whether the benefits are due to more efficient toxin
removal or other factors. The recommendations in common guidelines on
measuring the dose are inconsistent and confusing with considerable RRF and in
schedules other than 3 x/week.
3.3 How could dosing be improved?
How should treatment duration, frequency, blood flow, dialysate flow, and
convection volume be adjusted for optimal outcome?
AIMS OF THE STUDY
49
4 SUBJECTS AND METHODS
4.1 Patients
4.1.1 Hemodialysis treatment periods and modeling sessions
This thesis is a collection of observations from a small hospital providing adult
dialysis services for a district of about 50,000 inhabitants in Eastern Finland. The
observation time was nine years, from January 1, 1998 to December 31, 2006. The
material comprises 57 in-center hemodialysis treatment periods of 51 patients,
together 114.3 patient years. Short intervals as visitors to other dialysis centers do
not interrupt the treatment period and are included in the treatment years. The
patient characteristics are summarized in Table 2.
Table 2. Patient characteristics of the hemodialysis treatment periods (N = 57)
Mean SD Min Max
Females
%
38.6
Diabetics
%
42.1
Age
years
61.7
15.5 16.6 91.6
Height
cm
169
11
Weight
kg
75.1
18.2 44.2 123.6
BMI
kg/m2
26.1
5.5
16.3 43.7
Vt
L
31.9
6.8
20.5 50.3
Renal clearance mL/min 1.9
1.5
0.0
nPCR
0.24 0.73 1.74
g/kg/day 1.15
145 187
7.2
The number of individual patients is 51.
50
SUBJECTS AND METHODS
The total material comprises different overlapping groups of urea kinetic
modeling (UKM) sessions:
Study
I FREQUENCY
588 sessions of 35 patients 2004-2006
Study II INCREMENTAL
225 sessions of 30 patients with RRF 2004-2006
Study III EQUIVALENCY
619 sessions of 35 patients 2004-2006
Study IV AUTOMATION
205 IDM sessions of 33 patients 2004-2006
Study V ADEQUACY
1,200 sessions of 51 patients 1998-2006
The individual studies are referred to in the text by their Roman numbers,
equivalent to the original communications.
Table 3 shows the causes of discontinuation of the dialysis treatment periods.
Nineteen periods were still ongoing at the end of the observation period.
“Decision” refers to a unanimous decision by patient and physician to discontinue
renal replacement therapy.
Table 3. Hemodialysis treatment period durations and reasons for discontinuation
Duration (years)
N
%
Mean SD Min Max
Continuing
19 33.3
2.5
1.7 0.4 5.8
Death
16 28.1
2.3
1.6 0.6 6.9
Transplantation
8 14.0
1.4
1.3 0.6 4.6
Transfer to other unit
8 14.0
1.3
1.2 0.3 3.8
Transfer to peritoneal dialysis
3
5.3
2.1
1.4 0.7 3.5
Decision
3
5.3
0.8
0.3 0.6 1.1
The numbers include hemodialysis treatment periods ongoing on January 1, 1998 (from that date on)
and incident periods during the nine-year observation time until December 31, 2006 (unless
terminated earlier).
Some patients had more than one hemodialysis treatment period, occasionally
separated by several years. Study V (ADEQUACY) is based on average values of
the treatment periods. The other studies are based on individual UKM sessions.
SUBJECTS AND METHODS
51
4.1.2 Dialysis prescriptions
Dosing of dialysis, including treatment frequency, was prescribed by the author on
the basis of multiple criteria (weight, hydration status, predialysis blood urea
concentration and other laboratory values, eKt/V and stdK/V targets, and
patient's preferences). Renal diagnosis, comorbidity, functional status, waiting for
transplantation, age, nPCR or anticipated survival time were not used as dosing
criteria.
The patients were encouraged by a dietician to maintain a diet containing
protein 1.2 g/kg/day, but the actual dietary protein intake was not controlled.
nPCR – reflecting DPI – varied quite widely (Table 2).
4.1.3 Data collection
Dialysis data were collected in the routine care of hemodialysis patients
automatically online from dialysis machines, scales, and blood pressure meters by
the Finesse® dialysis information system (Fresenius) and stored in a Microsoft
Access® database. Another kidney patient information system developed by the
author combined data from the Finesse database and the Effica® hospital
laboratory system (Tieto Oyj), performed the UKM computations and created
monthly treatment summary reports.
4.2 Calculations
4.2.1 Urea kinetic modeling
Urea kinetic modeling with three blood samples and interdialysis urine collection
was performed routinely once per month (modeling session). Postdialysis blood
samples were taken at the termination of the session with a modified KDOQI
2006 slow-blood-flow technique [National Kidney Foundation 2006].
In Studies I-III the dialyzer urea clearance (Kd) of each treatment was
calculated with Michaels’ equation (36 on page 93) from the actual blood and
dialysate flow (Qb, Qd) and mass transfer area coefficient (K0A) of the dialyzer
model, based on several own blood side clearance measurements. In Study V K0A
52
SUBJECTS AND METHODS
values provided by the manufacturers were utilized. In Study IV readings from the
IDM device were used as Kd.
In the first study (I), computations were performed using the classic single pool
variable volume iterative urea kinetic model (spvvUKM, equations 33-35 on page
92) [Farrell and Gotch 1977, Gotch FA 1995b] with equilibrated postdialysis urea
concentration values calculated by the Tattersall method [Tattersall et al. 1996].
In Studies II-IV the iterative double-pool UKM model was used, modified from
the Solute-Solver program code version 1.97 with the Runge-Kutta numeric
integration procedure [Daugirdas et al. 2009]. The constants were the same as in
Solute-Solver:
blood water = 0.86 * blood volume
plasma water = 0.93 * plasma volume
“intracellular” compartment volume = 2/3 of total postdialysis volume; does not
change during the dialysis cycle
“extracellular” compartment postdialysis volume = 1/3 of total postdialysis
volume
intercompartment transfer coefficient (Kc, L/min) = 0.016 (/min) * total
postdialysis volume (L)
Plasma concentrations were converted into plasma water concentrations before
calculations and back to plasma concentrations in the tables and figures. In Studies
I-IV TAC and PAC used in calculating EKR/V and stdK/V are expressed as
“extracellular” pool water concentrations converted into plasma concentrations, in
Study V EKR/V and stdK/V are calculated from whole body water
concentrations.
UKM assumes that the patient is in a metabolic steady state, which was not
confirmed. The Borah equation [Borah et al. 1978] with Sargent’s modification
[Sargent 1983] was used in nPCR calculation.
In Studies I-IV calculation of the renal urea clearance Kr from interdialysis
urine volume and urea concentration was included in the V and G iteration loops.
To obtain the time-averaged concentration (TAC) and average predialysis
concentration (PAC), needed for calculating EKR and stdK, treatment parameters
– including frequency – were averaged over four weeks preceding and including
the modeling session. Treatments were then equalized by iterating the single or
double pool UKM concentration equation (single pool: 35 on page 92) sequentially
over average treatment time and average interval time until stabilizing of the
SUBJECTS AND METHODS
53
predialysis concentration. This procedure modifies an asymmetric schedule to an
evenly distributed one, but has no influence on the patient-specific values V, G,
and Kr. The effect of schedule asymmetry was not investigated in this thesis.
In Study V the Solute-Solver program was used as such and Kr was calculated
from dialysis cycle urine urea removal by using the average of post- and predialysis
urea concentrations.
4.2.2 Simulation and automation
The thesis is based on computer simulations of hemodialysis treatment. V, G, Kr
and weekly fluid removal requirement are the patient data needed to create the
dialysis prescription. They were derived from actual dialysis sessions by UKM. Kd,
td, and fr can be varied in simulated treatments, and concentrations, EKR/V, and
stdK/V calculated, assuming that variations in dialysis do not affect urea
generation rate. By numeric solution of the UKM equations it is also possible to
compute the required Kd or td to achieve desired concentrations, EKR/V and
stdK/V.
In Study IV, dialyzer mass area coefficient (K0A) was calculated at each session
from dialysate flow (Qd), blood flow (Qb) and online Kd by Michaels’ equation
[Daugirdas and Van Stone 2001, Ward et al. 2011]. The average K0A of each
dialyzer model was then used in simulations to compute the Qb and Qd to achieve
the required Kd. By successive simulations the computer generated a prescription
fulfilling multiple criteria based on the quality standards of care.
4.2.3 HEMO-equivalent EKR/V and stdK/V
In the standard-dose group of the HEMO trial [Eknoyan et al. 2002] the average
delivered eKt/V was 1.16. One third of the patients had RRF. To ensure a safety
margin for anuric patients, EKR/V and stdK/V values corresponding to eKt/V
1.20 in a conventional four-hour dialysis given three times per week (3 x 4 h/week)
schedule without RRF were calculated for each session as follows:
Single pool urea distribution volume (V1) was computed with the classic single
pool variable volume urea kinetic model (spvvUKM). Then Kd was solved from
Daugirdas’ eKt/V rate equation:
54
SUBJECTS AND METHODS
eKt/V = (Kd * td / V1) - a * (Kd * td / V1) / td + b
(20)
Kd = (eKt/V - b) * V1 / (td - a).
(21)
1.20 was assigned to eKt/V and 240 min to td. In sessions with arteriovenous
blood access a was 36 min and b 0.03, with venovenous access 28 min and 0.02
[Daugirdas 1993, Daugirdas 1995]. Dialysis treatment 3 x 4 h/week was simulated
for each modeling session with this Kd and Kr = 0. EKR/V and stdK/V were
then calculated in each simulated session.
4.2.4 Anthropometric normalization of ECC
In Study V nEKR and nstdK are ECC values normalized with body surface area
analogically to glomerular filtration rate or renal clearance, with mL/min/1.73m2 as
the unit:
nEKR = EKR / BSA * 1.73 and
(22)
nstdK = stdK / BSA * 1.73.
(23)
Daugirdas et al. have developed a method to obtain a BSA-normalized stdKt/V
[Daugirdas et al. 2008a, Daugirdas et al. 2010b]:
SAn-stdKt/V = stdKt/V * Vant / BSA / 20,
(24)
where Vant is anthropometric TBW in liters, BSA in m2 and the constant 20 the
mean of V/BSA (L/m2) in their material. Similarly, nEKRant and nstdKant can be
calculated using an anthropometric scaling factor Vant/BSA:
nEKRant = EKR/V * Vant / BSA * 1.73 and
(25)
nstdKant = stdK/V * Vant / BSA * 1.73
(26)
with appropriate unit conversion factors. Vant/BSA takes gender into
consideration. The unit of the anthropometrically normalized ECCs is
mL/min/1.73m2.
4.3 Computer applications
In Study V the double-pool computations were performed with a noncommercial
software Solute-Solver [Daugirdas et al. 2009], in the other studies with programs
SUBJECTS AND METHODS
55
written in the Basic programming language included in Microsoft Office Access®
2007 SP3. Microsoft Office Excel® 2007 SP3 was used to create the graphs. The
demonstration program HDOptimizer.exe was written in Microsoft Visual Basic®
2010.
4.4 Statistical methods
Continuous variables are expressed as means with standard deviations (SD) and
minimum and maximum values. Categorical variables are expressed as percentages.
Mortality is the number of deaths per 1,000 patient years of hemodialysis. Survival
times and Kaplan-Meyer curves are not presented.
In Study V, univariate and multivariable binary logistic regression analyses were
performed to identify variables associated with death. Variables with a univariate pvalue <0.10 were entered into the multivariable models. Odds ratios (ORs) and
95% confidence intervals (CIs) are reported. SPSS 22.0 and STATA 13.1 were used
in statistical calculations.
4.5 Ethical aspects
The thesis was performed with the permission of the medical director of the
hospital and is based on a retrospective analysis of register data collected and
utilized in the routine care of patients. There was no control group nor
randomization and no intervention. The patient data were anonymized and
deidentified prior to analysis. The author participated in the care of all patients.
56
SUBJECTS AND METHODS
5 RESULTS
EKR/V and stdK/V are continuous-equivalent clearances scaled by urea
distribution volume V. In Studies I-IV EKR/V was referred to as stdEKR. In
Study I stdK/V was referred to as stdKt/V.
5.1 Effect of frequency (I FREQUENCY)
The figures are based on a simulated patient with the average characteristics of 588
modeling sessions of 35 patients. In this population the values of stdEKR and
stdKt/V corresponding to eKt/V 1.20 – close to the standard dose in the HEMO
trial – were 3.34/week and 2.23/week respectively. Figures 1-4 represent the
patient dialyzed (simulated) with the HEMO standard dose-equivalent doses.
weKt/V is the sum of eKt/Vs in one week.
5.1.1 Effect on measures of dialysis dose
Figure 1 describes the effect of frequency on different measures of dialysis dose.
stdEKR and stdK/V can be increased by increasing frequency – without increasing
weekly treatment time or Kd. PAC and stdK/V are more sensitive to frequency
than TAC and stdEKR. Doubling the treatment frequency from 3 to 6 x/week
with equal weekly treatment time decreases PAC by 20%, but TAC only by 6%.
RESULTS
57
Figure 1. (not included in the original publication). Effect of treatment frequency on concentrations and
measures of dialysis dose. Weekly treatment time 12 h, Kd 200 ml/min, double pool, no RRF, no UF.
5.1.2 Effect on required treatment time
Figure 2 describes the effect of frequency on the weekly treatment time required to
achieve the HEMO standard dose equivalent ECCs with constant Kd. Much more
time is needed to achieve the stdKt/V target on a twice-weekly schedule than on a
thrice-weekly schedule. The effect of frequency is less steep with stdEKR as the
target. Weekly Kt/V is by definition not dependent on frequency.
With frequencies greater than 3 x/week, using stdKt/V as the target results in
shorter treatment times and higher concentrations than stdEKR (Figures 2-4).
58
RESULTS
Figure 2. Effect of treatment frequency on weekly treatment time required to achieve HEMO standard
dose equivalent targets. Kd 200 ml/min.
5.1.3 Effect on concentrations
With constant stdEKR, increasing frequency lowers PAC values (Figure 3). With
constant stdKt/V, TAC is considerably higher with higher frequency (Figure 4).
RESULTS
59
Figure 3. Effect of treatment frequency on predialysis concentration (C0 or PAC) with different HEMO
standard dose equivalent targets. Kd 200 ml/min, dose adjusted by treatment time.
Figure 4. Effect of treatment frequency on time-averaged concentration (TAC) with different HEMO
standard dose equivalent targets. Kd 200 ml/min, dose adjusted by treatment time.
60
RESULTS
5.2 Effect of residual renal function (II INCREMENTAL)
Figures 5-9 are based on a simulated patient with the average characteristics of 225
modeling sessions of 30 patients. Only sessions with RRF were included. stdEKR
= EKR/V.
In this cohort the values of stdEKR and stdKt/V corresponding to eKt/V 1.20
– close to the standard dose in the HEMO trial – were 3.48/week and 2.29/week
respectively. eKt/V 1.20 was achieved with an average of 187 mL/min dialyzer
clearance in a 3 x 4 h/week schedule (conventional dialysis). Additional measures
of RRF and both stdEKR and stdK/V increase linearly with renal urea clearance
(Kr). stdEKR increases in parallel with renal fractional clearance (rFC = Kr/V),
stdK/V in parallel with renal fractional solute removal rate (rFSRR) (Figure 5).
6.0
weKt/V
stdEKR
stdK/V
rFC
rFSRR
5.0
/wk
4.0
3.0
2.0
1.0
0.0
0.0
2.0
4.0
6.0
8.0
Kr ml/min
Figure 5. Effect of Kr on measures of RRF and dialysis dose. Standard dialysis (3 x 4 h/week, Kd 187
mL/min, eKt/V 1.20, UF 2.24 L).
5.2.1 Effect on required treatment time
The required treatment time to achieve the HEMO equivalent targets has a linear
inverse relationship to Kr (Figure 6). If the HEMO standard dose equivalent
RESULTS
61
stdEKR or stdK/V is used as the target, RRF may replace several hours of weekly
dialysis treatment time. stdK/V is affected by RRF more than stdEKR. In
incremental dialysis, with Kr = 4 mL/min the target stdK/V is achieved in one
half of the weekly treatment time required without RRF. Somewhat longer
treatment time is required to achieve the stdEKR target.
Figure 6. Dependence of required weekly treatment time on RRF. Frequency 3 x/week, Kd 187
mL/min.
5.2.2 Effect on concentrations
With constant stdEKR target, PAC decreases with increasing Kr; with a constant
stdK/V target, TAC increases with increasing Kr (Figures 7 and 8).
In Figures 6-9 the dialysis dose is varied incrementally by adjusting the
treatment time to achieve the HEMO standard dose equivalent stdEKR and
stdK/V targets.
62
RESULTS
30
PAC mmol/l
25
20
15
weKt/V 3.60/wk
stdEKR 3.48/wk
stdK/V 2.29/wk
10
0.0
2.0
4.0
6.0
8.0
Kr ml/min
Figure 7. Dependence of predialysis urea concentration PAC on RRF. Frequency 3 x/week, Kd 187
mL/min, dose adjusted by treatment time.
Figure 8. Dependence of TAC on RRF. Frequency 3 x/week, Kd 187 mL/min, dose adjusted by
treatment time.
RESULTS
63
Figure 9. Renal fraction of total urea excretion. Frequency 3 x/week, Kd 187 mL/min, dose adjusted by
treatment time.
5.2.3 Contribution to urea removal
Figure 9 presents the fraction (%) of total urea removal excreted by the kidneys.
With Kr = 4 mL/min, using the HEMO-equivalent stdK/V as target, almost one
half of the total urea excretion takes place through the kidneys. Dialysis and the
kidneys compete for solutes.
Ignoring RRF in UKM does not affect V or eKt/V, but leads to
underestimation of stdEKR, stdK/V, G and PCR. RRF lowers concentrations and
increases stdEKR and stdK/V. The average renal urea clearance of 2 mL/min
corresponds to 0.25-0.36 units of eKt/V.
64
RESULTS
5.3 Equivalent doses (III EQUIVALENCY)
The study is based on 619 modeling sessions of 35 patients with urea distribution
volumes of 14.4-57.5 L and nPCR values of 0.48-2.34 g/kg/day. stdEKR =
EKR/V.
5.3.1 ECC corresponding to HEMO standard dose
In the HEMO trial [Eknoyan et al. 2002] the mean eKt/V in the standard dose
group was 1.16±0.08 /session. In the present study the patients were “dialyzed”
(simulated) 3 * 4 h/week to eKt/V 1.2 by adjusting Kd. Kr was set at zero and
weekly ultrafiltration was equal to that in the actual sessions. The mean Kd was 189
mL/min. The mean HEMO standard dose equivalent stdEKR was 3.44/week and
stdK/V 2.40/week with moderate variation. Instead, TAC and PAC varied 6.8-6.5fold parallel to variations in G and nPCR (Table 4). The mean HEMO-equivalent
TAC 17.7 mmol/L was equal to the lower target in the NCDS.
Table 4. HEMO standard dose-equivalent TAC, PAC, stdEKR and stdK/V
Unit
Mean SD Min Max
renal urea clearance
mL/min
0.00 0.00 0.00 0.00
urine output
L/day
0.00 0.00 0.00 0.00
ultrafiltration
L/week
8.33 2.97 0.55 18.66
dialyzer urea clearance
mL/min
189
dialysis frequency
/week
3.00 0.00 3.00 3.00
dialysis duration
min
240
weekly dialysis time
h
12.0 0.0 12.0 12.0
equilibrated Kt/V
/session 1.20 0.00 1.20 1.20
time-averaged urea concentration
mmol/L
17.7 5.2 5.9 40.2
average predialysis urea concentration mmol/L
25.4 7.3 8.6 55.8
stdEKR
/week
3.44 0.08 3.23 3.92
stdK/V
/week
2.40 0.07 2.21 2.83
37
93
0 240
315
240
3 * 4 h/week, eKt/V 1.2 /session, Kd adjusted.
RESULTS
65
Dependence of stdEKR and stdK/V on eKt/V is not linear (Figure 10). With
increasing eKt/V, stdEKR increases more steeply than stdK/V. A 100-percent
increase in eKt/V from 0.80 to 1.60 results in a mere 43-percent increase in
stdK/V from 1.91 to 2.73/week. stdEKR is lower than weekly Kt/V and eKt/V.
ECCs behave differently from weekly Kt/V and eKt/V (Figures 2-9).
Figure 10. (not included in the original publication). Dependence of urea stdEKR and stdK/V on eKt/V.
Kr = 0, schedule 3 x 4 h/week, eKt/V adjusted by Kd.
5.3.2 Dialyzing to HEMO-equivalent ECC
Mean TAC and PAC were higher in women than in men when dialyzed to a
constant eKt/V, stdEKR or stdK/V corresponding to the HEMO standard dose
(Table 5).
66
RESULTS
Table 5. Mean TAC and PAC of urea in women and men dialyzed to HEMO-equivalent clearance
targets.
Dialysed to
eKt/V 1.2 (without RRF)
stdEKR 3.44/week
stdK/V 2.40/week
TAC
PAC
mmol/L
mmol/L
Women
18.7
26.8
Men
17.2
24.6
Women
18.9
26.3
Men
17.0
23.8
Women
19.8
27.1
Men
17.8
24.4
Gender
Dialysing to a constant TAC (17.7 mmol/L, the mean of HEMO standard dose
equivalent and equal to the NCDS lower target) results in a 7.1-fold variation in
stdEKR (1.15-8.12/week).
5.3.3 Solutes with different kinetics
“Extracellular” and “intracellular” distribution volumes of 13 and 26 L for urea and
3 and 9 L for β2-microglobulin and intercompartment transfer coefficients of 600
mL/min for urea and 40 mL/min for β2-microglobulin were used in twocompartment simulations for Figures 11-13 and Tables 6 and 7. Generation rates
were 200 µmol/min and 200 µg/min. The TAC units are correspondingly mmol/L
and mg/L. The generation rate has only a negligible effect on percent changes of
TAC and EKR.
Kt/V is linearly proportional to td, but concentrations and ECCs are not
(Figure 11). Concentrations can be decreased by increasing the frequency without
increasing the weekly treatment time (Figure 12).
RESULTS
67
Figure 11. (not included in the original publication). Dependence of concentrations on treatment time.
fr = 3 x/week, Kdurea = 200 mL/min, Kdβ2M = 30 mL/min. No RRF, no UF.
Figure 12. (not included in the original publication). Dependence of concentrations on treatment
frequency with constant weekly treatment time 12 h. Kdurea = 200 mL/min, Kdβ2M = 30 mL/min. No
RRF, no UF.
68
RESULTS
Table 6. Effect of blood and dialysate flow on Kd, TAC and EKR of solutes with different kinetics (not
included in the original publication)
K0A
Qb
Qd
mL/min mL/min mL/min
urea
Kd
TAC
EKR
mL/min Δ %
units/L Δ %
mL/min Δ %
1000
300
500
262
0
1000
300
100
100
1000
100
500
1000
100
40
β2M
14.3
0
14.0
0
-62
30.6 114
6.5
-53
100
-62
30.6 115
6.5
-53
100
91
-65
33.3 133
6.0
-57
300
500
36
0
110.2
0
1.8
0
40
300
100
31
-13
121.3
10
1.6
-9
40
100
500
32
-11
119.7
9
1.7
-8
40
100
100
29
-21
129.7
18
1.5
-15
Schedule 3 x 4 h/week, no RRF, no UF. Δ % is the difference from the first row of urea and β2M data.
According to Michaels’ equation, clearance of urea is more flow-dependent than
that of β2-microglobulin with low K0A. Reducing Qb from 300 to 100 mL/min or
Qd from 500 to 100 mL/min has an almost equal relative effect, but much greater
on urea than on β2-microglobulin (Table 6).
Table 7. Effect of dialysate flow and treatment time (not included in the original publication)
K0A
urea
Qb
Qd
td
mL/min mL/min mL/min
min
Kd
TAC
EKR
mL/min Δ %
units/L Δ %
mL/min Δ %
1000
300
500
240
262
0
14.2
0
14.0
0
1000
300
100
551
100
-62
14.2
0
14.0
0
1000
300
100
480
100
-62
16.1
13
12.4
-12
40
300
500
240
36
0
110.2
0
1.8
0
40
300
100
551
31
-13
55.9
-49
3.6
97
40
300
100
480
31
-13
63.6
-42
3.1
74
40
300
500
480
36
0
58.3
-47
3.4
89
β2M
Treatment frequency 3 x/week, no RRF, no UF. Δ % is the difference from the first row of urea and
β2M data.
The first and fourth rows of Table 7 describe the conventional 3 x 4 h/week
treatment with usual blood and dialysate flows as the references. If Qd is reduced
RESULTS
69
to 100 mL/min, treatment time has to be increased to 551 min to achieve the same
TACurea and EKRurea. With these changes in Qd and td, β2-microglobulin
concentration is halved and its EKR doubled. In the 8 h treatment with reduced
Qd TACurea increases 13% from the reference, but TAC of β2-microglobulin
decreases 42%, only slightly less than with full Qd (last row).
Kt is a patient-independent measure of the delivered dialysis dose. It can be
easily monitored with an IDM device. Figure 13 shows that increasing treatment
duration lowers β2-microglobulin concentration more than increasing frequency
with equal weekly Kt.
Figure 13. (not included in the original publication). Effect of frequency and time on concentrations
with equal weekly Kt (180 L). Dialyzer K0A 1000 mL/min for urea and 40 mL/min for β2-microglobulin,
Qb=350 mL/min, no RRF, no UF. A: weekly treatment time 12 h. B: frequency 3 x/week, td adjusted
by Qd (125-800 mL/min). 100% TACurea =14.7 mmol/L and TACβ2M =111 mg/L.
70
RESULTS
5.4 Creating the prescription (IV AUTOMATION)
The study is based on 205 UKM sessions of 33 patients with ionic dialysance data.
Readings from the IDM device were used as Kd in UKM. stdEKR = EKR/V.
5.4.1 Prescribed and delivered dose
If the prescribed and delivered Kd are equal, the delivered spKt/V (measured by
classic spvvUKM or Daugirdas’ equation) is higher than the prescribed one
because V calculated by spvvUKM is smaller than the anthropometric total body
water used in the prescription [Daugirdas et al. 2003, Depner et al. 1992,
Kloppenburg et al. 2001]. It is easy to achieve the prescribed dose (Table 8).
Table 8. Mean Kd, td, anthropometric TBW, modeled V and prescribed and measured Kt/V (not
included in the original publication)
Kd
td
TBW
V
mL/min
min
L
L
202
297
40.1
33.4
Kt/VPre
Kt/VDau
spKt/V
eKt/V
1.54
1.80
1.83
1.47
On-line ionic clearance from the IDM device has been used as Kd in calculating the prescribed Kt/V
(Kt/VPre) from anthropometric TBW (Watson) and actual td.
5.4.2 Optimization procedure
V, G, Kr, and weekly fluid removal requirement are the patient data needed to
create the dialysis prescription. They were derived from the actual dialysis sessions
by double-pool UKM. The goal of the optimization procedure was to generate
from each dataset a prescription fulfilling 12 criteria (Table 9).
Qb and td were continuous variables. The frequency values were 2, 3, 3.5
(alternate day), 4, 5, 6 and 7 x/week and dialysate flow 300, 500 and 800 mL/min.
Prescription generation started with simulations with minimum fr, Qb, Qd, and td.
If more dialysis was needed, Qb was increased first, then Qd to 500 mL/min, then
td, then Qd to maximum, and finally treatment frequency. Weekly UF volume and
the dialyzer (K0A) were held constant within each simulation. RRF (Kr) was taken
into account.
RESULTS
71
Table 9. Optimization criteria
min max
treatment frequency /week
2
7
treatment time
min
240
300
dialysate flow
mL/min
300
800
blood flow
mL/min
50
stdEKR
/week
b
3.44
stdK/V
/week
b
2.35
TAC
mmol/L
20.0
PAC
mmol/L
30.0
a
287
a
Average value. The blood flow upper limit used in each optimized session was 90% of the patient's
maximum blood flow during the previous four weeks.
b
Average value. The minimum stdEKR and stdK/V were defined individually for each session to
correspond to eKt/V 1.2 in a 3 x 4 h/week schedule without RRF.
5.4.3 Automatic prescriptions
A computer program for creating a dialysis prescription based on patient data (V,
G, Kr, weekly UF) from previous actual sessions and on 12 freely definable criteria
was developed. A simplified version of the program can be downloaded from
http://www.verkkomunuainen.net/optimize.html, accessed November 12, 2015. It
has not been validated clinically and is intended to be used only for demonstrating
and testing the optimization method, not for treating patients.
The simulated optimized treatments differed considerably from both the
conventionally prescribed actual and the simulated HEMO-equivalent ones (Tables
10 and 11). By optimization, 173 (84%) of the sessions fell into the 3 x/week
schedule, 15 (7%) needed more; in 17 (8%) 2 x/week was sufficient (Table 10).
These proportions of course depend on the optimization criteria (Table 9).
In 43 sessions (21%) the optimized dialysis dose was determined by the
concentration limits. The HEMO-equivalent clearance was not enough to keep
TAC and PAC below the defined upper limits (20 and 30 mmol/L) if nPCR was
greater than 1.3 g/kg/day. Figure 14 summarizes the results.
72
RESULTS
Table 10. Optimized sessions: frequency distribution and values by frequency (average ± SD)
fr
Sessions
/week
Kr
N mL/min
nPCR
stdEKR
stdK/V
g/kg/day
/week
/week
2
17 3.2 ±1.3 1.09 ± 0.22 3.52 ± 0.23 2.35 ± 0.18
3
173 0.6 ±1.1 1.06 ± 0.24 3.51 ± 0.19 2.44 ± 0.14
3.5
4
sum
12 0.6 ±0.9 1.35 ± 0.28 3.91 ± 0.44 2.74 ± 0.24
3 2.1 ±1.1 1.74 ± 0.12 4.87 ± 0.40 3.37 ± 0.11
205
Abbreviations: fr, treatment frequency; Sessions, number of sessions in each frequency category; Kr,
renal blood water urea clearance; nPCR, normalized protein catabolic rate. With the new scheduling
the number of sessions decreased to 202.
Table 10 may be interpreted as follows: With normal nPCR two sessions per
week is sufficient only if the patient has moderate RRF, but with high nPCR high
frequency is required to achieve the TAC and PAC targets despite RRF, and this is
reflected in high clearances.
Figure 14. TAC, PAC, stdEKR and stdK/V plotted against nPCR in the optimized sessions.
RESULTS
73
Table 11. Actual and simulated sessions
treatment frequency
average
minimum
maximum
SD
treatment duration
average
minimum
maximum
SD
eKt/V
average
minimum
maximum
SD
stdEKR
average
minimum
maximum
SD
stdK/V
average
minimum
maximum
SD
TAC
average
minimum
maximum
SD
PAC
average
minimum
maximum
SD
weekly treatment time
average
SD
weekly dialysate consumption
average
SD
74
Actual
HEMO
Optimized
/week
/week
/week
/week
3.11
2.00
4.45
0.33
3.00
3.00
3.00
0.00
2.96
2.00
4.00
0.33
min
min
min
min
297
243
485
40
240
240
240
0
250
240
299
17
1.47
0.93
2.39
0.26
1.20
1.20
1.20
0.00
1.18
0.76
2.03
0.18
/week
/week
/week
/week
4.65
3.08
6.31
0.61
3.44
3.23
3.61
0.08
3.56
3.23
5.29
0.29
/week
/week
/week
/week
2.96
2.12
3.78
0.32
2.35
2.15
2.53
0.07
2.47
2.17
3.47
0.20
mmol/L
mmol/L
mmol/L
mmol/L
12.4
4.7
25.7
3.6
16.5
6.8
30.0
4.6
15.8
6.8
20.1
3.6
mmol/L
mmol/L
mmol/L
mmol/L
19.3
7.5
36.3
5.5
24.2
9.8
44.7
6.7
22.8
9.8
30.0
5.2
h
h
15.4
2.4
12.0
0.0
12.3
1.5
L
L
459
65
360
0
302
95
RESULTS
5.5 Prognostic value (V ADEQUACY)
The study is based on 57 hemodialysis treatment periods of 51 patients. EKR/V
and stdK/V are continuous-equivalent clearances scaled to urea distribution
volume. nEKR and nstdK are continuous-equivalent clearances normalized with
BSA, nEKRant and nstdKant in addition with Vant.
5.5.1 Association of ECC with death risk
Equivalent renal urea clearance (EKR) [Casino and Lopez 1996] and standard
clearance (stdK) [Gotch 1996, Gotch et al. 2000] take treatment frequency and
residual renal function (RRF) into account and were intended for use in comparing
dialysis doses in different schedules and to continuous dialysis and renal function.
Table 12. Association of patient characteristics and dialysis dose measures with death risk in 57
hemodialysis treatment periods of 51 patients
Univariate
Mean
SD Min
Max
p
OR
95% CI
Age
years
61.6 15.5 16.7
91.6
0.103 1.038 0.993 - 1.085
Weight
kg
75.1 18.2 44.2 123.6
0.525 0.989 0.957 - 1.023
BMI
kg/m2
26.1
5.5 16.3
43.7
0.198 0.924 0.819 - 1.042
BSA
m2
1.84 0.25 1.31
2.34
0.872 0.823 0.078 - 8.727
V
L
31.8
6.7 20.5
50.3
0.637 1.021 0.936 - 1.113
nPCR
g/kg/day
1.15 0.24 0.73
1.74
0.058 0.065 0.004 - 1.095
nKr
mL/min/1.73
m2
1.7
1.4
0.0
6.0
0.861 0.963 0.631 - 1.469
nEKR
mL/min/1.73 m2
12.5
1.3
8.4
16.4
0.044 0.611 0.379 - 0.988
nstdK
mL/min/1.73 m2
8.5
1.0
6.2
12.2
0.183 0.638 0.330 - 1.235
m2
15.1
2.3
8.3
20.3
0.113 0.806 0.617 - 1.053
nstdKant mL/min/1.73 m2
10.2
1.6
6.1
14.3
0.232 0.785 0.527 - 1.168
EKR/V
/week
4.35 0.64 2.36
5.82
0.033 0.326 0.117 - 0.912
stdK/V
/week
2.93 0.39 1.73
3.88
0.059 0.205 0.040 - 1.060
fr
/week
2.9
0.3
2.0
3.7
0.413 0.503 0.097 - 2.606
td
h/week
13.5
2.3
7.7
18.4
0.077 0.786 0.602 - 1.027
nEKRant mL/min/1.73
RESULTS
75
Mortality was significantly associated with EKR/V and nEKR but not with
stdK/V or nstdK (Table 12). In multivariable analysis, EKR/V was the only
variable having an association with death risk (OR=0.326, CI=0.117-0.912,
p=0.033).
5.5.2 Interaction between nPCR and ECC
By definition (Equations 16-19 on page 38)
G = EKR/V * TAC * V
(27)
G = stdK/V * PAC * V
(28)
(EKR/V) / (stdK/V) = PAC / TAC.
(29)
In hemodialysis nPCR is generally calculated as also in the present study by the
Borah equation [Borah et al. 1978] with Sargent's modification [Sargent 1983]:
nPCR = (9.35 * G + 0.294 * V) / (V / 0.58),
(30)
where nPCR is expressed in g/kg/day, G in milligrams of urea-N/min and V in L.
By substituting G from Equations 27 and 28 and using appropriate unit conversion
factors we obtain
nPCR = 0.0151 * EKR/V * TAC + 0.171 and
(31)
nPCR = 0.0151 * stdK/V * PAC + 0.171,
(32)
where nPCR is in g/kg/day, EKR/V and stdK/V in /week and TAC and PAC in
mmol/L. V will be eliminated. nPCR is high if urea concentration is high despite
high or normal clearance. Mathematical linking inevitably contributes to the
correlations between nPCR and EKR/V and stdK/V (Table 13).
Figure 15 describes the linear regression between nPCR and EKR/V in the
present material. To eliminate the confounding effect of nPCR on the dosemortality relationship, the material was split to two groups with roughly equal
mean nPCR but different mean EKR/V. The line separating the groups appears in
Figure 15. Table 14 shows that the difference in mortality between the low and
high dose groups is still significant.
76
RESULTS
Figure 15. Linear regression between nPCR and dialysis dose (EKR/V) and the line separating the
groups of Table 14.
Table 13. Spearman’s correlations, significant at the 0.01 level (2-tailed)
Weight
Weight
BMI
BSA
1 0.854 0.950
1 0.658
V nPCR nEKR
0.748
nstdK nEKRant nstdKant
0.352
BMI
0.854
0.455
BSA
0.950 0.658
1
0.817
0.364
V
0.748 0.455 0.817
1
0.436
nPCR
1
nEKR
0.436
0.530
0.393
0.427
0.430
0.521
stdK/V
-0.475
-0.354
0.493
0.519
0.535
0.609
1
0.929
0.694
0.711
0.566
0.631
0.929
1
0.569
0.686
0.351
0.509
nstdK
0.352
nEKRant
0.453 0.393 0.430
0.493 0.694
0.569
1
0.962
0.821
0.850
nstdKant
0.530 0.427 0.521
0.519 0.711
0.686
0.962
1
0.706
0.809
EKR/V
-0.475 0.535 0.566
0.351
0.821
0.706
1
0.961
stdK/V
-0.354 0.609 0.631
0.509
0.850
0.809
0.961
1
RESULTS
0.364
0.453
EKR/V
77
Table 14. Dialysis treatment periods divided into two groups with roughly equal mean nPCR
EKR/V
Low
Mean
High
SD
Mean
SD p-value
Age
years
60.8 13.2
62.5 17.7
0.668
Weight
kg
77.1 21.2
72.9 14.7
0.393
BMI
kg/m2
26.5
25.7
4.4
0.595
BSA
m2
1.86 0.27
1.81 0.22
0.441
V
L
33.7
29.8
5.1
0.024
nPCR
g/kg/day
1.19 0.28
1.12 0.19
0.283
nKr
mL/min/1.73 m2
2.0
1.4
1.4
1.4
0.102
nEKR
mL/min/1.73 m2
12.1
1.5
13.0
1.0
0.005
nstdK
mL/min/1.73 m2
8.3
1.1
8.7
0.9
0.240
nEKRant
mL/min/1.73 m2
14.2
2.4
16.2
1.7
0.001
nstdKant
mL/min/1.73
m2
9.8
1.7
10.7
1.3
0.023
EKR/V
/week
3.99 0.59
4.72 0.45 <0.001
stdK/V
/week
2.75 0.38
3.12 0.30 <0.001
Treatment frequency /week
6.5
7.5
2.8
0.4
3.1
0.2
0.006
12.6
2.5
14.4
1.7
0.003
Treatment time
h/week
Treatment periods
n
29
28
Females
%
31.0
46.4
0.233
Diabetics
%
37.9
46.4
0.516
ending to death
%
37.9
17.9
0.092
Patient years
n
49.8
64.5
Deaths
n
11
5
Mortality
/1000 py
221
78
78
0.049
RESULTS
5.5.3 Association of ECC and mortality with gender
Women had significantly higher nPCR, EKR/V and stdK/V and lower mortality
than men, but differences in BSA-based ECCs were not significant (Table 15).
Table 15. Dialysis treatment periods by gender
Women
Men
Mean
SD
Mean
SD
p-value
Age
years
63.3
14.5
60.6
16.1
0.529
Weight
kg
65.2
15.3
81.2
17.4
0.001
BMI
kg/m2
25.7
5.9
26.3
5.3
0.694
BSA
m2
1.66
0.17
1.95
0.22
<0.001
V
L
26.1
3.6
35.3
5.7
<0.001
nPCR
g/kg/day
1.23
0.23
1.10
0.24
0.043
mL/min/1.73
m2
1.9
1.4
1.6
1.4
0.467
mL/min/1.73
m2
12.4
1.1
12.7
1.5
0.401
nstdK
mL/min/1.73
m2
8.2
0.7
8.7
1.1
0.066
nEKRant
mL/min/1.73 m2
14.8
1.9
15.4
2.6
0.349
nstdKant
mL/min/1.73 m2
9.8
1.2
10.5
1.7
0.082
EKR/V
/week
4.64
0.57
4.17
0.62
0.005
stdK/V
/week
3.07
0.36
2.85
0.39
0.036
Treatment periods
n
22
35
nKr
nEKR
%
13.6
37.1
Patient years
ending to death
n
50.6
63.7
Deaths
n
3
13
Mortality
/1000 py
59
204
RESULTS
0.055
0.040
79
6 DISCUSSION
6.1 Urea kinetic modeling
The present thesis is based on urea kinetic modeling. A single-pool model was used
in Study I, because the Solute-Solver program was not yet available [Daugirdas et
al. 2009]. Double-pool UKM used in Studies II-V takes into account all essential
factors affecting the urea concentration profile as a function of time. Simulating
hemodialysis and creating fairly accurate prescriptions is possible with kinetic
modeling, but the patient’s G, V, and Kr may vary between sessions and there are
significant error sources in measuring them.
With equal clearance-based dosing the differences in urea concentrations are
manifold due to differences in generation rate (Study III). Anorexia is common in
uremia. In theory, using a constant urea concentration as the target – as in the
NCDS – could lead to a vicious circle as presented by [Gotch et al. 1990] and in
the introduction of Study III: the underdialyzed patient loses his or her appetite →
dietary protein intake (DPI), PCR, G and concentrations decrease → the dialysis
dose will be further diminished. This implies that after decreasing the dialysis dose,
DPI, PCR, and G decrease relatively even more than clearance (K) – improbable
with current practices (Equation 2c on page 19).
Dialyzer clearance Kd is the most difficult input parameter in UKM. Its errors
have only a minimal effect on Kt/V, but a proportional effect on V and G. Kd can
be calculated from Qb, Qd and dialyzer K0A with Michaels’ equation (36 on page
93), but manufacturers report K0A inconsistently. Hematocrit, dialyzer structure,
clotting or reuse may modify it. In Studies I-III K0A for each dialyzer model was
determined by a limited number of own blood-side measurements. K0A reported
by the manufacturers was used in Study V. The errors in K0A cause relatively small
errors to Kd. The errors of G and V caused by inaccurate Kd cancel each other out
in EKR/V and stdK/V.
The main message regarding UKM is that although the ionic dialysance may not
be exactly equal to urea clearance, it may well be used as Kd in UKM and in
creating prescriptions, because it is derived from circumstances similar to those in
80
DISCUSSION
which it will be applied. This method was used in Study IV. IDM does not replace
UKM, but makes it more useful.
6.2 Continuous-equivalent urea clearance
Weekly values of dialysis dose are required for comparing different schedules, but
as seen in Figures 2 (Study I, page 59), 5 and 6 (Study II, pages 61-62), weekly
eKt/V (sum of the eKt/Vs of one week's sessions) underestimates the therapeutic
significance of frequency and ignores RRF.
EKR/V and stdK/V are continuous-equivalent clearances scaled to urea
distribution volume. At first sight, EKR/V calculated from the time-averaged urea
concentration over the whole week seems to be the correct measure of continuousequivalent clearance. Currently, however, stdK/V is more popular, perhaps
because the numbers are closer to the corresponding values in CAPD. Gotch
[Gotch 2001, Gotch 2004] and Casino [Casino 2001] postulate that the relation
between Kt/V and EKR is linear and that EKR fails to reflect the effect of dialysis
frequency. In Figure 10 of Study III (page 66) the relationship between eKt/V and
double-pool EKR/V is not exactly linear and Figures 1 (Study I, page 58) and 12
(Study III, page 68) show that with constant weekly treatment time, increasing
frequency lowers TAC and increases double pool EKR/V.
Increasing frequency or RRF lowers concentrations and shortens the weekly
treatment time required to achieve the EKR/V and stdK/V targets (Figures 2 in
Study I and 6 in Study II, pages 59 and 62). stdK/V is more sensitive to frequency
and RRF than EKR/V. With increasing frequency above 3 x/week, using stdK/V
as the target results in higher concentrations (PAC and TAC) than using EKR/V
(Figures 3 and 4, page 60). With EKR/V as the target, PAC decreases with
increasing RRF (Figure 7, page 63). When using stdK/V as the target, TAC
increases with increasing RRF (Figure 8, page 63).
Increasing dialyzer clearance (K0A, Kd, Qb, Qd) is an inefficient way to increase
stdK/V [Roa and Prado 2004]. With simulated 3 x 4 h/week schedule without
RRF in Study III, increasing Kd by 34% from 191 mL/min to 256 mL/min
(eKt/V from 1.2 to 1.6) resulted in a 12% fall of average PAC from 24.2 to 21.4
mmol/L and a 13% rise of stdK/V from 2.35 to 2.66/week (Figure 10, page 66).
The stdK/V values in hemodialysis are roughly equal to the fractional clearance
K/V in CAPD; EKR/V is higher, but in Study V EKR/V had better predictive
DISCUSSION
81
value than stdK/V. HD and CAPD have other differences in addition to the
intermittency, e.g. different characteristics of the dialysis membrane and utilization
of osmotic instead of pressure gradient in convection. Continuous-equivalent
measures of urea clearance may function between different intermittent HD
schedules, but not between HD and CAPD. Aiming at equal clearance values in
HD and CAPD is artificial [Garred et al. 1994b]. EKR/V and stdK/V are not as
commensurable as was desired [Kjellstrand and Twardowski 1999].
In Study III comprising the most representative material the EKR/V and
stdK/V values corresponding to eKt/V 1.20 in a conventional 3 x 4 h/week
schedule were 3.44 and 2.40/week respectively. The KDOQI guidelines for
hemodialysis adequacy have recently been updated to take RRF and UF into
consideration and recommend stdK/V 2.3/week as the target for hemodialysis
schedules other than thrice weekly [National Kidney Foundation 2015]. Improved
versions of the empirical stdK/V equations that include UF and RRF are rather
complex and need estimation of V [Daugirdas et al. 2010a]. SRI as a continuousequivalent dialysis dose measure – recommended by EBPG 2007 – is inconsistently
documented and not addressed in the present thesis. The current guidelines give
no recommendations on EKR.
In conclusion, continuous-equivalent clearances are the most logical measures
to assess the effect of dialysis on urea concentrations. EKRurea seemed to be more
closely associated with outcome than stdKurea.
6.3 Scaling
Distribution volume V is an essential parameter in urea kinetic modeling and
reflects the patient’s size, but is useless in comparing clearances of substances with
different distribution volumes.
The anthropometric TBW is usually higher than the modeled V. There is a
certain safety margin in the prescribed Kt/V if anthropometric TBW is used as V
(Table 8 in Study IV, page 71). Online monitoring of spKt/V is currently possible
in real time. Modeled V should preferably be used instead of anthropometric TBW
with IDM to avoid “overdialysis”.
In the HEMO trial, women benefited from higher eKt/V but men did not. This
is at least partially associated with scaling by V [Ramirez et al. 2012]. We have
either to accept that the dose-and-effect relationship is different in men and
82
DISCUSSION
women or to choose a different scaling factor. BSA – used recently also in dialysis
[Debowska et al. 2015] – may be better than V [Lowrie et al. 2005, Lowrie et al.
2006] providing more dialysis to women and children, who also will benefit from it.
Women had higher urea concentrations than men with equal V-scaled dialysis
doses (Table 5 in Study III, page 67). Dialyzing to an equal concentration would
deliver more Kt/V to women. In Study V the anthropometrically normalized
ECCs were approximately equal between genders, but the V-scaled significantly
higher in women. However, the continuous-equivalent clearances normalized with
BSA were not more closely associated with mortality than the V-scaled ones (Table
14 in Study V, page 78), possibly due to the small number of patients.
6.4 Protein catabolic rate and dialysis dose
PCR reflects dietary protein intake (DPI), which correlates with nutritional status
and outcome [National Kidney Foundation 2000]. In a recent large registry
material mortality decreased with increasing nPCR until 1.3 g/kg/day with
constant Kt/V [Ravel et al. 2013]. Often – and also in Study V – a positive
correlation between dialysis dose and protein catabolic rate has been observed.
This may indicate cause and effect [Buur et al. 1995, Lindsay et al. 1993, Marcus et
al. 1999, Spanner et al. 2003] or mathematical coupling [Gotch F 1995a, Harty et al.
1993, Stein and Walls 1994, Uehlinger 1996, Venning et al. 1993] or that dosing of
dialysis has been guided by urea concentrations (reverse causality, fear of high urea
concentrations). All these factors may have a role in Study V. With low dialysis
doses the cause and effect relationship may be valid, but probably not with current
dose levels [Di Iorio et al. 1996, Kloppenburg et al. 2004]. In the HEMO trial the
effect of dialysis dose on nPCR and the role of mathematical coupling were
estimated to be small [Rocco et al. 2004].
Concentrations of several uremic toxins correlate with the protein catabolic rate
in dialysis patients [Eloot et al. 2013]. Morton and Singer propose that the dialysis
dose should be normalized to the metabolic rate [Morton and Singer 2007, Singer
and Morton 2000]. Depner states that more oral protein intake demands more
dialysis [Depner 1991a]. Gotch recommends spKt/V 0.9-1.0 for patients with low
G and higher for those with high G, about equal numeric value to nPCR in the
3 x/week schedule [Gotch 1990, Gotch and Sargent 1985, Gotch et al. 2000].
Patients with high dietary protein intake, high protein catabolic rate and high G
have high urea concentrations when dialyzed with a commonly accepted clearance
DISCUSSION
83
(Kt/V, EKR/V or stdK/V; Study III). It may be justified to increase the dialysis
dose if urea concentrations are high. Study IV describes how this could be done.
Protein catabolic rate is taken into account by cutting high urea concentrations.
Continuous-equivalent measures of dialysis dose are needed, because the adjusting
procedure may change the frequency. In simulated dialysis sessions the HEMO
standard-dose equivalent ECC was insufficient to maintain time-averaged
concentration (TAC) and average predialysis concentration (PAC) of urea below
the defined upper limits (20 and 30 mmol/L) if nPCR was higher than
1.3 g/kg/day. Concentration limits may help in selecting patients likely to benefit
from high frequency, but with the optimization criteria used more than three
sessions per week were needed in only 7% of cases (Study IV).
In summary, we do not know the optimal or critical upper limits of TAC and
PAC or whether such exist. After seeing a high predialysis urea concentration it is
usually fairly simple to intensify the treatment, if we believe that it is justified. High
concentration is due either to low clearance or to high generation rate. In both
cases the dialysis dose needs to be increased if the hypothesis that patients with
high nPCR benefit from higher than normal clearance-based dose actually holds
true. This has not been confirmed empirically.
6.5 Treatment duration and frequency
Increasing duration increases Kt/V linearly, but the relationship between duration
and concentration is nonlinear (Figure 11 in Study III, page 68). In simple
simulations with the double-pool model increasing treatment duration from 240 to
480 min causes concentrations to decrease by 30-50%, those of β2-microglobulin
only slightly more than those of urea. Concentrations can be decreased by 7-22%,
PAC more than TAC, by increasing the frequency without increasing the weekly
treatment time (Figure 12, page 68).
These examples show that urea and β2-microglobulin react similarly to changes
in duration and frequency despite their different kinetics. Increasing duration and
frequency have also been combined, but the results of the RCTs are not promising
[Rocco et al. 2011, Rocco et al. 2015].
In the alternate day schedule the serious complications associated with the long
interdialysis interval are avoided [Jun et al. 2013].
84
DISCUSSION
The variation of duration and frequency in Study V was rather small and no
conclusion can be drawn as to which one is more effective in improving the
outcome, but theoretical calculations favor increasing duration for better removal
of uremic toxins.
6.6 Residual renal function
In hemodialysis patients, RRF may contribute to total urea removal by more than
50% (Figure 9 in Study II, page 64). According to urea kinetics, RRF may replace
several hours of weekly dialysis treatment time in a conventional thrice-weekly
schedule, if HEMO-equivalent EKR/V and stdK/V values are used as targets in
incremental dialysis (Figure 6, page 62). Each mL/min of renal urea clearance
corresponds to about 30-60 min of session time. Each weekly dialysis hour replaces
about 0.7 mL/min of lacking renal urea clearance. Other uremic solutes behave
differently. The positive effect of RRF is probably greater than its contribution to
urea clearance.
RRF decreases TAC and especially PAC. Kr is an input parameter in UKM and
is needed in the calculation of urea generation rate and PCR. Kr is automatically
included in continuous-equivalent clearances if derived from UKM. Urea as a
marker makes RRF and dialysis commensurable in a safe way: renal function
expressed as urea clearance is “qualitatively better” than equal dialysis urea
clearance. In incremental dialysis it is important to check Kr frequently.
The concept of incremental dialysis is compatible with the old concept of [Babb
et al. 1972] and the more recent results of [Khan et al. 2002]. A drawback is that
patients who have begun with it are reluctant to increase their dialysis time when
RRF fades. When to initiate dialysis and how to preserve RRF is not addressed in
this thesis.
6.7 Solutes with different kinetics
Doubling of td lowers TAC of differently behaving solutes by 30-50% (Figure 11
in Study III, page 68). Increasing frequency (with constant weekly treatment time)
from 3 to 7 x/week lowers the TAC of urea and β2-microglobulin by 7-9%, PAC
by somewhat more (Figure 12, page 68). Both time and frequency are somewhat
unspecific means to control uremic retention solutes with different kinetics.
DISCUSSION
85
Decreasing Qd from 500 to 100 mL/min or Qb from 300 to 100 mL/min
decreases urea diffusive clearance by 62% and increases TACurea by 114-115%, but
decreases β2-microglobulin clearance by only 11-13% and increases TACβ2M by 910% (Table 6, page 69). Decreasing Qd from 500 to 100 mL/min combined with
increasing time from 240 to 480 min changes urea and β2-microglobulin values in
opposite directions (Table 7, page 69). Changes in flows cause much greater effects
on clearances and concentrations of urea than on those of middle molecules. This
decreases the significance of Kt/Vurea and the value of high Qb. With equal urea
clearance (EKR) or concentration (TAC), concentrations of middle molecules are
lower with more gentle treatment (lower Qb and/or Qd and longer td; Figure 13,
page 70). The calculations are in accordance with the analysis of [GoldfarbRumyantzev et al. 2002]. Favoring high-efficiency dialysis and adhering to the
single-pool Kt/V may partially explain the poor outcomes in the USA in the
1980's.
The low dialysate flow technique may be suitable for nocturnal home
hemodialysis on every other day. In more frequent schedules the complications
associated with blood access may outweigh the advantages due to enhanced middle
molecule clearance [Jun et al. 2013, Weinhandl et al. 2015].
Uremic toxins, including β2-microglobulin, do not necessarily obey double-pool
kinetics. The distribution volumes and intercompartment transfer coefficients
cannot be modified. Increasing Kd of middle molecules may be possible by
increasing convection. The effect on outcome of a decrease of concentrations of
uremic toxins depends of course on the correlation of toxicity with concentration.
It is unclear which is the most useful strategy – increasing convection or time or
frequency. All of these have been reported to improve outcome. According to the
simulations in Study III increasing duration seems to be a more effective means to
decrease middle molecule concentrations than increasing frequency. However,
short daily and infrequent long nocturnal dialyses are very different treatment
modalities with only outcome as the common measure and are not suitable for all.
High frequency and long duration with slightly reduced blood and dialysate flows
were combined in the (underpowered) FHN nocturnal trial with negative effects
[Rocco et al. 2015]. If we knew more about the kinetics of uremic toxins and the
concentration-dependence of their toxicity, we might prefer one strategy over the
other.
In conclusion, although ECC is probably the best measure of the effect of
dialysis on urea concentrations, applying it to other substances detracts from its
86
DISCUSSION
value and the significance of urea as a marker solute and shows that the interest
should be directed from clearances of urea to concentrations of true uremic toxins.
6.8 Adequacy
In most observational controlled studies, increasing clearance, time, frequency or
convection has had a positive effect on both survival and soft endpoints. In RCTs
such as HEMO and especially in the FHN trials the patients recruited may not
have been a representative sample of the whole hemodialysis population. The dose
targeting bias also affected the HEMO results [Greene et al. 2005]. After HEMO
the doses have still increased despite its results [Miller et al. 2010].
There are only few reports correlating outcome directly with continuousequivalent dose measures referred to and discussed in the literature review section
2.6.6 [Barreneche et al. 1999, Manotham et al. 2006, Rocco et al. 2011, The FHN
Trial Group 2010]. In a cohort of 191 quotidian home hemodialysis patients
survival was independently associated positively with stdK/V up to over
5.00/week without plateauing [Lockridge et al. 2012]. In the short daily arm of the
FHN trial stdK/V was higher and outcome better in the high frequency group
[The FHN Trial Group 2010], but in the frequent nocturnal arm the differences in
stdK/V between the test and control groups were even greater and the long-term
outcome worse in the higher dose group [Rocco et al. 2015].
Continuous-equivalent dose measures combine session frequency, the dose of
each session and residual kidney function. The best measure of dialysis adequacy is
the one which is most closely associated with outcome. In Study V comparing
ECCs it was EKR/V. Mortality was also associated significantly with nEKR, but
not with stdK/V or nstdK. Associations of EKR and stdK with survival have not
been compared earlier.
The effects of concentration fluctuations, frequency, and RRF are reflected
differently in EKR/V and stdK/V (Studies I and II). Simulations with substances
behaving differently from urea (Tables 6 and 7 in Study III, page 69) impair the
value of methods based on urea clearance. EKR/Vurea and stdK/Vurea do not
accurately reflect middle molecule removal. Probably the outcomes cannot be
improved by increasing urea clearance from the current level, but we should
concentrate on the more difficult to remove molecules. Other pathways in addition
to dialysis may also be involved in their elimination, and it may be possible to
DISCUSSION
87
influence the generation rate of some of them. We need more information on the
kinetics and effects of real uremic toxins and should compare their concentrations
in different treatment modes with equal urea clearance as the common dose
measure. Monitoring UV light absorption of the effluent dialysate may offer a new
viewpoint if Kt/Vurea is abandoned as the reference.
In Study V urea clearance and PCR correlate positively with outcome and with
each other. nPCR is associated with survival directly and with the dialysis dose
through the “fear of high urea concentrations” effect – an example of possible
mechanisms behind the dose-targeting bias [Greene et al. 2005]. Patients with high
nPCR may benefit from higher dose by this mechanism. nPCR and dialysis dose
seem to have a synergistic association with survival.
6.9 Limitations
Inaccuracy of the single-pool model affects the simulations in Study I. K0A-values
in Studies I-III are based on own blood-side clearance measurements with
remarkable dispersion. The K0A-values based on IDM used in Study IV also vary
within each dialyzer model. In Study V the results were unadjusted for comorbidity
(except diabetes), dialysis vintage, vascular access, blood pressure, laboratory
values, epoetin use, and many other possible confounding factors. The dialysis
dose was not randomly assigned as it is not in most retrospective observational
registry studies. The role of convection was ignored; high-flux dialyzers were used
only in about 10% of treatments. As expected, there was a correlation between age
and mortality, but it was statistically insignificant.
The most serious limitation is the small number of patients in Study V. No
robust conclusions can be drawn. The aim was to compare the predictive value of
specific risk factors in the same population, not treatments.
6.10 New questions
Do patients with high PCR really benefit from high clearance? The prescription
algorithm (Study IV) should be tested on patients. Studies on the association of
ionic dialysance, weekly BSA-normalized Kt and dialysate UV light absorption with
mortality and other descriptors of treatment outcome are needed. Also, it would be
interesting to measure the light absorption of the effluent dialysate with other and
88
DISCUSSION
multiple wavelengths reflecting the kinetics of true uremic toxins instead of uric
acid and urea (Donadio et al. 2014). The ECC dose measures should be compared
in a larger material than that used in Study V. Could the high first half year
mortality be decreased by an incremental approach? The peak concentration
hypothesis is still unconfirmed. More data is needed on the kinetics and toxicity of
uremic retention solutes. The effect of treatment time, frequency, and convection
on outcomes should be tested with equal BSA-normalized dose (weekly nKt).
DISCUSSION
89
7 CONCLUSIONS
7.1 Is high mortality in hemodialysis due to low dose?
In each study of the thesis mean EKR/V and stdK/V were considerably higher
than the corresponding HEMO standard dose equivalent values. Thus, the rather
high mortality (140 deaths/1,000 patient years) – although lower than in the USA –
was probably not mainly due to universal underdialysis. An association between
dose and mortality was also detected in this population. The mortality might have
been lower if the lowest doses had been higher – assuming that the association
reflects causality. However, dose is not the only descriptor of treatment quality.
7.2 How should the dialysis dose be measured?
Residual renal function contributes significantly to urea removal and even more to
the removal of true uremic toxins. Taking it into consideration by incremental
dialysis relieves the burden of the treatment. ECC is a rational way to note
treatment frequency and RRF. EKR seems to be more closely associated with
mortality than stdK.
The treatment dose has to be scaled to patient size. BSA may be a better scaling
factor than urea distribution volume. Normalizing with BSA gives more dialysis to
women and children and they also benefit from it.
No single absolutely correct dialysis dose measure exists. Urea does not
universally represent the behavior of uremic toxins. Small dialyzable molecules like
potassium are important in the short term. If the patient dies rapidly due to
retention of small molecules, large molecules with slow harmful effects are not
significant. EKR and stdK handle treatment frequency and RRF appropriately, but
are not ideal predictors of treatment effectiveness when based solely on urea
kinetics. Hemodialysis adequacy cannot be described with only one number.
Dialyzer urea clearance is a good descriptor of the method. The delivered
dialysis dose (efficiency of toxin removal) can be defined technically as weekly
90
CONCLUSIONS
dialyzer urea clearance, normalized with BSA (nKturea), e. g. 180 L/week/1.73m2
corresponding to about 14 mL/min of EKR, 3.6/week of EKR/V and 2.4/week
of stdK/V in a 3 x 4 h/week schedule, which guarantees sufficient removal of
small molecules. In fact, this is like weekly spKt/V, but with BSA as the scaling
factor instead of V. It is less than 180 L/week/1.73m2 of continuous clearance.
The target can be safely reduced by nKrurea (L/week/1.73 m2). Kt is easily
monitored with an online device based on ionic dialysance. Dialyzer clearance and
weekly treatment time determine the delivered dose externally, reflecting
consumption of resources. Blood samples, UKM and computers are not needed. A
distinction must be made between dose and effect. ECC, Kt/V and URR reflect
patient-dependent effects of treatment, modified by treatment schedule and
individual intercompartment transfer coefficients and compartment volumes.
7.3 How could dosing be improved?
Improving hemodialysis outcomes may be possible by increasing clearance,
duration, frequency, and convection. Increasing treatment duration with constant
weekly Kturea lowers concentrations of middle molecules. Increasing frequency
without increasing weekly treatment time decreases concentrations of all solutes,
PAC more than TAC, but may increase inconvenience, complications, and costs.
The possible beneficial effect of higher frequency is not based solely on the
efficiency of solute removal. Fluctuation of concentrations and volumes and the
compartment effects (disequilibrium) are associated with frequency and may affect
outcome. However, stdK may overestimate the benefits of increased frequency and
result in higher concentrations when used as the dosing target in frequent dialysis.
An alternate day schedule may be a useful compromise between daily and
conventional schedules.
Urea concentration depends heavily on its generation rate, which is also an
independent prognostic factor. Instead of urea clearances we should concentrate
on the concentrations of true uremic toxins.
The outcomes probably cannot be improved by increasing urea removal from
the current level. Future investigations with constant delivered dose (weekly nKt)
will hopefully reveal the best strategies (duration, frequency or convection) to
control the long-term effects of uremic toxins. The relative clearances of small and
large molecules can be adjusted by blood and dialysate flow but not by time or
frequency.
CONCLUSIONS
91
8 UKM EQUATIONS
1
Qf


Kd

Kr

Qf

G Ct  Kd  Kr Qf 


Vt  Qf  td  1  G C0 Kd  Kr Qf 
  1



 


 Kr    C0  Ct  VtVt 
G
1  
Ct  C0

V 0 Qf  td
V0

Vt 
Vt
Kd  Kr Qf
Qf


 Kr 
G
Kd  Kr Qf
Kr  

(33)


(34)

1 

V 0 Qf  td
V0

Kd  Kr Qf
Qf


(35)
Classic single-pool variable volume urea kinetic model equations [Gotch FA 1995b]. V0 and Vt are the
distribution volumes at the beginning and end of treatment; Qf is the rate of volume contraction during
dialysis (= ultrafiltration rate), td is treatment duration; G is the interdialytic urea generation rate; Kd
and Kr are the dialyzer and kidney urea clearances; C0 and Ct are the urea concentrations at the
92
EQUATIONS
beginning and end of treatment, α is the rate of interdialytic volume expansion calculated by the total
interdialytic weight gain divided by the length of the interdialytic interval, θ.
  KQbA  QdQdQb 

e
1 

Kd  Qb K A Qd Qb
  Qb  Qd  Qb 
 Qd 
e
0
0
(36)
Michaels’ equation [Daugirdas and Van Stone 2001, Ward et al. 2011]. e is the base of the natural
logarithm.
EQUATIONS
93
94
ACKNOWLEDGEMENTS
9 ACKNOWLEDGEMENTS
My warmest gratitude goes to
Professor Emeritus Jukka Mustonen for his encouraging approach regarding this
work as supervisor and for his help in many theoretical and practical problems,
Heini Huhtala, MSc, for her patient guidance into the secrets of scientific writing
and help in statistical analysis,
Professor Ilkka Pörsti and Docent Satu Mäkelä, the members of my thesis followup group, for encouragement and valuable advice,
Docents Kaj Metsärinne and Risto Ikäheimo, the reviewers, for constructive
criticism which essentially improved the text,
Erkki Lampainen, MD, PhD, my informal mentor in clinical work with kidney
patients, and Mika Taskinen, MD, my successor at Savonlinna Central Hospital, for
stimulating discussions,
Tiina Kurikkala, RN, Eija Korhonen, RN, Terhi Siitonen, RN and all other
members of the dialysis team of Savonlinna Central Hospital for decades of
cooperation in the successes and adversities of the everyday work,
my mother Alli Vartia (1904-1993) for her encouragement to me when at school,
which enabled me to find an interesting job, and my sons Risto and Lauri for their
confidence in me.
Finally, I express my deepest gratitude to my beloved wife Ansa for fifty years
of patience and understanding. She has taken care of all domestic matters while I
was preoccupied by my own thoughts and interests. This thesis would have been
absolutely impossible without her contribution.
The English of the thesis was checked interactively by Virginia Mattila, MA.
The thesis was financially supported by The Finnish Kidney Foundation.
Savonlinna, March 2016
ACKNOWLEDGEMENTS
95
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ORIGINAL COMMUNICATIONS
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Nephrol Dial Transplant (2009) 24: 2797–2803
doi: 10.1093/ndt/gfp177
Advance Access publication 22 April 2009
Effect of treatment frequency on haemodialysis dose: comparison
of EKR and stdKt/V
Aarne Vartia
Savonlinna Central Hospital, Keskussairaalantie 6, 57120 Savonlinna, Finland
Correspondence and offprint requests to: Aarne Vartia; E-mail: [email protected]
Abstract
Background. Haemodialysis outcome cannot be improved
by increasing the dialysis session dose above the current
standard in conventional schedules. Promising results have
been reported from daily dialysis, but the optimal dose has
not been established.
Methods. Weekly eKt/V, equivalent renal clearance (EKR)
and stdKt/V were compared retrospectively in 588 complete urea kinetic modelling sessions of 35 haemodialysis patients. Equivalent values of EKR and stdKt/V corresponding to the standard and high doses of the HEMO
study were defined by computer simulation. The effect of
frequency on the dose measures was demonstrated by simulating different schedules.
Results. EKR and stdKt/V take into consideration both
frequency and RRF, but appreciate them differently. The
values of EKRc (EKR in millilitres per minute, normalized to distribution volume 40 l), stdEKR (EKR in litres
per week divided by urea distribution volume in litres)
and stdKt/V corresponding to eKt/V 1.20—close to the
standard dose in the HEMO study—were 13.2 ml/min/40
l, 3.34/wk and 2.23/wk, respectively. stdKt/V appreciates
frequency more than EKR. A spreadsheet was created to
compute the dialysis session time to achieve the EKR or
stdKt/V target when the basic urea kinetic variables are
known.
Conclusions. Haemodialysis efficiency can be increased
by increasing frequency. EKR and stdKt/V are more appropriate than weekly eKt/V as measures of dialysis dose
in different schedules. With increasing frequency, stdKt/V
as the dosing target results in shorter treatment times and
higher concentrations than EKR.
Keywords: computer simulation; dialysis dosing; EKR; eKt/V; stdKt/V
Kt/V is a measure of a single dialysis session. Weekly
Kt/V (wKt/V) is the sum of the Kt/Vs of 1-week sessions. It
is—in theory—the same whether the patient is dialysed 6 h
two times per week or 2 h six times with the same dialyser
clearance (Kd). According to numerous reports, the latter
schedule yields better outcomes.
In CAPD (continuous ambulatory peritoneal dialysis)
patients with total ‘weekly Kt/V’ 2.0 do equally well as
patients on HD with wKt/V 3.6. What we call ‘weekly
Kt/V’ in CAPD is the fractional clearance (K/V): continuous clearance K divided by distribution volume V relating
it to body size. The unit is ‘/wk’. The only problem is estimation of V, which in intermittent HD comes from the urea
kinetic model (UKM). Fractional clearance can be used as
a measure of renal function, too.
Equilibrated Kt/V (eKt/V) takes the compartment disequilibrium into account and helps in avoiding underdialysis
in short high-efficiency treatments and in small patients, but
weekly eKt/V (weKt/V)—like wKt/V—ignores the significance of frequency.
Weekly Kt/V and weKt/V have been reported to be higher
in short daily HD with equal weekly treatment time and
other dialysis parameters [2–4]. The dialyser clearance may
decrease during the session due to clotting and accumulation of material on the membrane, so, on average, it may
be higher in shorter sessions with equal blood and dialysate
flow. On the other hand, wKt/V [5] and weKt/V [6] have
also been reported to remain unchanged on switching from
three to six times per week treatment with the same weekly
treatment time.
In addition to wKt/V and weKt/V, several methods have
been proposed for evaluation of the equivalency of renal
function and different intermittent and continuous dialysis
techniques:
weekly urea reduction ratio (URR) [5–7]
weekly solute removal index (SRI) [8–10]
Introduction
weekly fractional solute removal (FSR) [11]
According to the HEMO study [1], the outcome of
haemodialysis (HD) cannot be improved by increasing the
session dose (Kt/V) above the current standard of a three
times per week schedule.
EKR (equivalent renal clearance, Casino and Lopez) [12]
stdKt/V (Gotch) [13]
nKt/V (Depner) [14].
C The Author [2009]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
For Permissions, please e-mail: [email protected]
2798
Chen et al. [7] observed that weekly Kt/V values of
CAPD patients and weekly URRs of HD patients were
similar to each other. Cheng et al. [10] reported higher
weekly URR values for CAPD than for HD patients despite markedly higher wKt/V in HD. Maduell et al. [5] and
Williams et al. [6] observed higher weekly URR in short
daily than in conventional treatment with the same weekly
treatment time and wKt/V or weKt/V.
The optimal dose measure for schedules other than three
times weekly has not been established [15]. The European
guidelines [16] recommend stdKt/V, EKR and SRI. Unfortunately, SRI has conflicting definitions.
The objective of the current retrospective observational
analysis is
1. to determine the EKR and stdKt/V values corresponding to the standard and high doses of the HEMO study
and
2. to compare EKR and stdKt/V as measures of dialysis dose in symmetric schedules with different frequencies.
Subjects and methods
Detailed description of the abbreviations, symbols, definitions and equations is presented in the Appendix.
Data have been gathered by a dialysis information system in the routine
care of HD patients. No randomization, control group or study protocol
has been used.
Urea kinetic modelling with three blood samples and interdialysis urine
collection was done once per month (modelling session). Postdialysis
blood samples were taken at the termination of the session with a modified
KDOQI slow-blood-flow technique [17]. Postdialysis urea concentrations
were converted to equilibrated ones by the Tattersall method [18]. Then
all calculations were done using the classic single-pool variable-volume
urea kinetic model (spvvUKM) [19,20] with the equilibrated postdialysis
values. The urea generation rate (G) and distribution volume (V) are
required in computing the protein equivalent of total nitrogen appearance
(nPNA), EKR and stdKt/V.
Dialysis sessions
The analysis is based on 588 data sets collected between 1 January 2004
and 31 December 2006 from 35 prevalent HD patients having at least one
complete urea kinetic modelling session after the first 4 weeks of dialysis.
All patients were white Europeans. The modelling sessions are described
in Table 1.
Residual renal function (RRF)
RRF is expressed as renal urea clearance Kr (ml/min) and renal fractional
urea clearance rFC (/wk). The entire interdialysis urine was collected. The
calculation of Kr is described in the Appendix. If Kr was below 1 ml/min
in three consecutive measurements, Kr and diuresis were stated as zero
and urine was not collected in subsequent modelling sessions.
Dialysis dose
All variables, including G, Vt, Kr, rFC, nPNA, EKR and std/V, are based
on equilibrated postdialysis concentrations although explicitly noted only
on eKt/V.
Dialysis dosing is expressed in four ways:
(1) EKRc: EKR normalized to distribution volume of 40 l, expressed in
ml/min units (Casino and Lopez)
(2) stdEKR: EKR divided by distribution volume, expressed in /wk units
to facilitate comparison to stdKt/V
(3) stdKt/V (Gotch) in /wk units
A. Vartia
Table 1. Modelling sessions
Data
Number of sessions
Sessions with RRF
Females
Age
Height
Postdialysis weight
Total body water (Watson)
Kinetic urea distribution
volume
Urea generation rate
nPNA
Diuresis
Renal urea clearance
Renal fractional urea
clearance
Unit
Value/
average
SD
Min
Max
%
%
Years
cm
kg
l
l
588
32.8
37.2
65.1
169
78.7
39.5
40.0
16.0
10
18.7
8.1
7.4
16.0
150
43.3
24.6
20.2
91.6
187
134.5
61.0
65.2
µmol/min
g/kg/day
l/day
ml/min
/wk
218
1.01
0.19
0.65
0.16
73
0.24
0.35
1.29
0.27
76
0.45
0.00
0.00
0.00
547
2.13
1.69
5.10
0.98
(4) weekly eKt/V: the sum of the eKt/Vs of 1-week treatment sessions,
in /wk units.
Time-averaged concentration (TAC) and average predialysis concentration (PAC), needed in calculating EKR and stdKt/V, cannot be derived
from a single modelling session. Treatment parameters were averaged
over 4 weeks preceding and including the modelling session. The actual
dialyser urea clearance (Kd) of each treatment was calculated from actual
blood and dialysate flow (Qb, Qd) and the mass transfer area coefficient
(KoA) of the dialyser [21]. KoA is based on several blood side blood water
clearance measurements of each dialyser model. Dialysers were used only
once.
Treatments were equalized by iterating the spvvUKM concentration
equation [19] sequentially over average treatment time and average interval
time until plateauing of the predialysis concentration (see the Appendix).
This procedure modifies an asymmetric schedule to an evenly distributed
one, but has no influence on the patient-specific values.
Simulations
The effect of treatment frequency on the measures of dialysis dose was
studied by computer simulations. They are based on the classic spvvUKM
with the patient-dependent values G, Vt and Kr from the modelling session
and varying treatment values, keeping weekly ultrafiltration unchanged
and assuming that dialysis has no effect on urea generation and renal
function.
Statistical methods
Microsoft Excel 2002 software was used in calculating minimum and
maximum values and standard deviations and in creating the graphs.
Results
Equivalent doses
Equivalent values corresponding to the standard and high
dialysis doses of the HEMO study were determined
by simulating a conventional dialysis with a symmetric
3 × 4 h/wk schedule and eKt/V 1.20 and 1.60 in the
study material (Table 2), respectively. Dialysis intensity was
adjusted by dialyser clearance. Numbers in the table are
averages of the 588 sessions. The most important parameters are in bold.
The simulated values of EKRc, stdEKR and stdKt/V corresponding to eKt/V 1.20—close to the standard dose in the
HEMO study (1.16)—are 13.2 ml/min/40 l, 3.34/wk and
Effect of treatment frequency on haemodialysis dose
2799
Table 2. Average equivalent measures of HEMO standard and high doses
Data
Unit
Actual equalized
HEMO standard
3×4h
HEMO high
3×4h
HEMO high
3×5h
HEMO high
6 × 2.5 h
Dialysis frequency
Dialysis time
Weekly dialysis time
Predialysis concentration
Equilibrated postdialysis
concentration
Time-averaged concentration
Dialyser clearance
Ultrafiltration volume
Equilibrated Kt/V
Weekly equilibrated Kt/V
EKRc (Casino and Lopez)
stdEKR
stdKt/V (Gotch)
/wk
min
h
mmol/l
mmol/l
3.12
292
15.2
19.8
5.5
3.00
240
12.0
23.3
8.6
3.00
240
12.0
20.3
5.3
3.00
300
15.0
20.1
5.4
6.00
150
15.0
15.4
7.8
mmol/l
ml/min
l
12.7
213
2.73
1.59
4.93
16.9
4.26
2.63
16.1
200
2.84
1.20
3.60
13.2
3.34
2.23
12.9
266
2.84
1.60
4.80
16.4
4.14
2.54
12.8
213
2.84
1.60
4.80
16.5
4.16
2.57
11.6
213
1.42
0.80
4.80
18.6
4.68
3.48
/wk
ml/min/40 l
/wk
/wk
2.23/wk, respectively. Weekly eKt/V and stdEKR are remarkably higher than stdKt/V, far above the range achieved
in CAPD. The values of EKRc, stdEKR and stdKt/V
corresponding to eKt/V 1.60—close to the high dose in
the HEMO study (1.53)—are 16.4 ml/min/40 l, 4.14/wk
and 2.54/wk, respectively.
It may be difficult to achieve eKt/V 1.60 in 4 h. The
last two columns of Table 2 represent the HEMO high dose
equivalent values in symmetric 3 × 5 h/wk and 6 × 2.5 h/wk
schedules, respectively. Uraemic toxicity is probably related to concentrations. Predialysis and TACs are lower
with higher frequency, although generation and elimination rates, treatment time and dialysis fluid consumption
are equal. This may be interpreted as better efficiency
and is reflected in higher EKR and stdKt/V, but not in
weKt/V.
Effect of frequency
The simulations are based on weekly eKt/V, stdEKR and
stdKt/V as measures of dialysis dose.
Figure 1 describes the effect of frequency on different
measures of dialysis dose in a patient with average characteristics of the study material (Table 1). Frequency affects
stdKt/V more than stdEKR. Weekly eKt/V is not dependent
on frequency.
Figures 2–4 represent the patient dialysed with the
standard-equivalent doses defined in Table 2.
Figure 2 describes the effect of frequency on the weekly
treatment time required to achieve the standard-equivalent
doses with constant Kd. Much more time is needed to
achieve the stdKt/V target in a two times per week schedule
than in three times per week. The effect of frequency is less
steep with stdEKR as the target dose measure.
With higher frequency, using stdKt/V as the target results in higher concentrations (C0 and TAC) than stdEKR
(Figures 3 and 4).
The curves in Figures 1–4 are based on a simulated
patient with G = 218 µmol/min, V = 40.0 l, Kr =
0.65 ml/min (Table 1) and UF = 8.5 l/wk (Table 2).
With the spreadsheet DoseOpt.xls in http://www.
Fig. 1. Effect of treatment frequency on measures of dialysis dose. Weekly
treatment time 12 h, Kd 200 ml/min.
verkkomunuainen.net/optimize.html, the dialysis prescription can be planned individually.
Discussion
The current analysis is based on the UKM. One of the
parameters in this model is renal urea clearance, which is
lower than the glomerular filtration rate.
HD urea kinetics can be described rather accurately by
a two-pool model that requires several blood samples or a
dialysate urea monitor. Using single-pool UKM with dialyser clearance and equilibrated postdialysis concentration
as input parameters is a practical shortcut, although incorrect in theory. It involves mixing of single- and double-pool
models and overestimates Vt to compensate the difference
between dialyser clearance and whole body patient clearance to give a ‘correct’ eKt/V. This concept was used as the
2800
Fig. 2. Effect of treatment frequency on weekly treatment time required to
achieve different HEMO standard dose equivalent targets. Kd 200 ml/min.
Fig. 3. Effect of treatment frequency on predialysis concentration (C0)
with different HEMO standard dose equivalent targets. Kd 200 ml/min,
dose adjusted by treatment time.
reference in a HEMO pilot study in choosing the method to
measure the delivered dialysis dose [22]. Inaccuracy of the
single-pool model affects the equalization procedure and
simulations in the current study.
The current material differs in several aspects (age,
weight, race, sex distribution, anthropometric total body
water, maximum rFC) from the HEMO study. In a different
population, the values of EKR and stdKt/V corresponding
to eKt/V 1.2 and 1.6 may be different.
Weekly measures of dialysis dose are required in comparing different schedules, but as seen from Table 2 and the
figures and argued in the literature [13,14], weekly eKt/V
underestimates the therapeutic significance of frequency.
A. Vartia
Fig. 4. Effect of treatment frequency on time-averaged concentration
(TAC) with different HEMO standard dose equivalent targets. Kd 200 ml/
min, dose adjusted by treatment time.
In CAPD, stdKt/V and stdEKR are equal to the fractional
clearance (‘weekly Kt/V’). In standard HEMO-equivalent
dialysis (Table 2), the average stdKt/V (2.23 /wk) is comparable to the stdKt/V of CAPD patients. Possibly the greater
unphysiology (fluctuation of volume and concentrations,
compartment disequilibrium) and different sieving profiles
of the membrane have to be compensated by a slightly
greater dose in HD to achieve equal outcome.
According to the European guidelines [16], in anuric
patients, treated by three times per week dialysis, the prescribed target eKt/V should be at least 1.2, and for patients
with renal function or those with dialysis schedules other
than three times per week, weekly dialysis dose should be
at least equivalent to an SRI of 2. In a symmetric schedule,
SRI—as defined in the guidelines—is equal to stdKt/V.
In the current material, the SRI or stdKt/V value corresponding to a delivered eKt/V of 1.2 is considerably higher.
The difference corresponds to 42 min of session time (198
versus 240 min) in a symmetric three times per week schedule with a Kd of 200 ml/min. SRI 2.00/wk corresponds to
eKt/V 0.99. With significant RRF, a lower value of SRI or
stdKt/V may be acceptable, because it, based on the UKM,
underestimates renal function.
Future investigation is needed to elucidate whether increasing the dialysis dose above the equivalents of the
HEMO standard dose by increasing the frequency is of
any prognostic benefit and whether increased dose or decreased unphysiology [23] is more important in frequent
dialysis.
stdKt/V appreciates frequency more than EKR. If diminished unphysiology is the most essential advantage of
frequent dialysis, then dosing is best guided by stdKt/V
resulting in shorter weekly treatment time with increasing
frequency, but if dose is important, then EKR is more suitable resulting in lower concentrations.
Conflict of interest statement. None declared.
Effect of treatment frequency on haemodialysis dose
Appendix
Abbreviations and symbols
UKM = urea kinetic model
spvvUKM = single-pool variable volume UKM
RRF = residual renal function
HD = haemodialysis
CAPD = continuous ambulatory peritoneal dialysis
Qb = blood flow
Qd = dialysate flow
t = observation period duration
td = dialysis session duration
ti = dialysis interval duration
fr = dialysis session frequency
G = generation rate
E = removal rate
K = clearance
Kd = diffusive blood water dialyser clearance
KoA = mass transfer area coefficient of the dialyser
Kr = renal clearance
rFC = renal fractional clearance
C = concentration
C1 = concentration at the beginning of the observation
period
C2 = concentration at the end of the observation period
C0 = concentration at the beginning of a dialysis session
Ct = equilibrated postdialysis concentration
C02 = concentration at the beginning of the next dialysis
session
TAC = time-averaged concentration, computed using equilibrated postdialysis concentration
PAC = average predialysis concentration, average C0
Cu = urine concentration
V = distribution volume
V1 = distribution volume at the beginning of the observation period
V0 = distribution volume at the beginning of a dialysis
session
Vt = distribution volume at the end of a dialysis session
V02 = distribution volume at the beginning of the next
dialysis session
Va = average distribution volume
Vu = interdialysis urine volume
VG = fluid accumulation during the observation period
VGd = fluid accumulation during a dialysis session, usually
negative
VGi = fluid accumulation between dialysis sessions
WGi = weight gain between dialysis sessions
UF = ultrafiltration volume (positive, if fluid is removed)
URR = urea reduction ratio
SRI = solute removal index
FSR = fractional solute removal
tFSRR = average total fractional solute removal rate (renal
+ dialysis)
wtFSR = weekly total fractional solute removal (renal +
dialysis)
RUR = renal urea removal, amount of urea in interdialysis
urine
DUR = amount of urea removed in a dialysis session
Kt/V = dialysis session dose, single pool
2801
eKt/V = equilibrated dialysis session dose
wKt/V = weekly Kt/V
weKt/V = weekly eKt/V
EKR = equivalent renal urea clearance, a measure of dialysis dosing defined by Casino and Lopez [12]
EKRc = EKR normalized to a urea distribution volume of
40 l
stdKt/V = a measure of dialysis dosing defined by Gotch
[13]
stdEKR = EKR divided by V; comparable to stdKt/V
NBW = normal body weight
PNA = protein equivalent of total nitrogen appearance
nPNA = normalized PNA
Definitions and calculations
VGi = WGi (in conjunction with the actual modelling
session)
(A.1)
VGi = UF
(in the equalized schedule)
(A.2)
VGd = −UF
(A.3)
V0 = Vt + UF
(A.4)
V02 = Vt + VGi
(A.5)
Va = (V0 + Vt)/2
(A.6)
RUR = Vu∗ Cu
(A.7)
DUR = V0∗ C0 − Vt∗ Ct + td∗ G
(A.8)
G = (V02∗ C02 − Vt∗ Ct + RUR)/ti
(A.9)
rFC = Kr/Vt
(A.10)
Kt/V = Kd∗ td/Vt
(A.11)
wKt/V = fr∗ Kt/V
(A.12)
weKt/V = fr∗ eKt/V
(A.13)
nKt/V = 0.92∗ fr∗ (1 − exp(−1.1∗ Kt/V))
NBW = Vt/0.58
(A.14)
(assuming 1 litre weighs 1 kg)
(A.15)
nPNA = PNA/NBW.
(A.16)
The Sargent modification [24] of the original Borah equation [25] was used in calculating PNA.
EKR (equivalent renal urea clearance) and stdKt/V are
based on the definition of clearance:
K = E/C.
(A.17)
In steady state E = G, so
K = G/C.
(A.18)
In EKR, the term C of equation (A.18) is the time-averaged
concentration (TAC), in stdKt/V, the average predialysis
concentration (PAC). According to the definition, stdKt/V
2802
A. Vartia
is normalized by dividing the value of equation (A.18) by
the distribution volume V. Dividing EKR by V yields a
variable called here as stdEKR (eqKRt/V in [26]):
stdEKR = G/TAC/Va
(A.19)
stdKt/V = G/PAC/V0.
(A.20)
The unit of stdEKR and stdKt/V is /wk. To ensure conformity with wtFSR, predialysis volume (V0) is used in
stdKt/V, average volume (Va) in stdEKR.
EKRc is stdEKR multiplied by a ‘normal’ distribution
volume 40 l and divided by the number of minutes in a
week (10 080) [12]:
EKRc = 3.97∗ stdEKR.
(A.21)
The unit of EKRc is ml/min/40 l.
Weekly total fractional solute removal (wtFSR) is the
amount of urea removed by dialysis and the kidneys during
1 week divided by the average predialysis amount of urea
in the body. More generally
tFSRR = E/(PAC∗ V0).
(A.22)
As seen from equations (A.20) and (A.22), tFSRR =
stdKt/V, if E = G. wtFSR is tFSRR with week as the time
unit like in stdKt/V. Only stdKt/V is used in the Results
section.
Kr is computed by searching for the value that yields C02
from Ct. Calculations of G, V and Kr are included in the
same iteration loop:
Vt = ASV
‘arbitrary starting value
Repeat
Vp = Vt
‘previous Vt
G = ((Vt + VGi)∗ C02 −
‘different from classic
Vt∗ Ct + RUR)/ti
UKM
Kr = fK(Ct, C02 , Vt,
‘binary search (declared
VGi, ti, G)
below)
Vt = fVt(C0, Ct, −UF,
‘spvvUKM Vt equation
td, Kd, Kr, G)
Until Abs((Vt − Vp)/Vt) < 0.00001
The parameters of function fVt() are C1, C2, VG, t, Kd,
Kr and G. It returns Vt.
function fK(C1, C2, V1,
VG, t, G)
K1 = 0
K2 = MAX
Repeat
K = (K1 + K2)/2
Cc = fCt(C1, V1, VG,
t, K, G)
If Cc > C2 Then
‘computation of clearance
by binary search
‘lowest possible value of
clearance K
‘highest possible value of
clearance K
‘spvvUKM concentration
equation
‘Cc = calculated
concentration
K1 = K
Else
K2 = K
End If
Until Abs(Cc − C2)/C2 < 0.00001
fK = K.
Equalizing the schedule to a symmetric one
In column ‘Actual equalized’ of Table 2, dialysis frequency,
dialysis time, weekly dialysis time, dialyser clearance, ultrafiltration volume, equilibrated Kt/V and weekly equilibrated Kt/V are averages of the 4-week averages associated
with each modelling session.
Treatments are equalized by iterating the classic
spvvUKM concentration equation sequentially over the average treatment time and average interval time until plateauing of C0, using Kr, G and Vt from the modelling session
and average Kd and average UF:
C0 = ASV
‘arbitrary starting value
Repeat
Cp = C0
‘previous C0
Ct = fCt(C0, Vt+AvgUF, ‘spvvUKM concentration
−AvgUF, Avgtd,
equation, dialysis
AvgKd, Kr, G)
C0 = fCt(Ct, Vt, AvgUF, ‘spvvUKM concentration
Avgti, 0, Kr, G)
equation, interval
Until Abs(C0 − Cp)/C0 < 0.00001
The equalization procedure modifies C0 and Ct and facilitates calculations of TAC, PAC, EKR, stdKt/V and
wtFSR. PAC is C0 computed by equalizing. TAC is
the cycle area_under_the_time/concentration_curve divided by the cycle duration, calculated from the equalized values according to Casino and Lopez [12]. RUR
is calculated by multiplying the equalized interdialysis
area_under_the_time/concentration_curve (used in TAC
calculation) by Kr. In a symmetric schedule,
wtFSR = fr∗ (RUR + DUR)/(C0∗ V0).
(A.23)
The FSR concept enables assessment of the renal and
dialysis components of urea elimination separately without
dialysate collection.
References
1. Eknoyan G, Beck GJ, Cheung AK et al. Effect of dialysis dose and
membrane flux in maintenance hemodialysis. N Engl J Med 2002;
347: 2010–2019
2. Galland R, Traeger J, Arkouche W et al. Short daily hemodialysis and
nutritional status. Am J Kidney Dis 2001; 37(Suppl 2): S95–S98
3. Galland R, Traeger J, Delawari E et al. Daily hemodialysis versus standard hemodialysis: TAC, TAD, weekly eKt/V, std(Kt/V) and PCRn.
Home Hemodial Int 1999; 3: 33–36
4. Goldfarb-Rumyantzev AS, Leypoldt JK, Nelson N et al. A crossover
study of short daily haemodialysis. Nephrol Dial Transplant 2006; 21:
166–175
5. Maduell F, Navarro V, Torregrosa E et al. Change from three times
a week on-line hemodiafiltration to short daily on-line hemodiafiltration. Kidney Int 2003; 64: 305–313
6. Williams A, Chebroly S, Ing T et al. Early clinical, quality-of-life, and
biochemical changes of ‘daily hemodialysis’ (6 dialyses per week).
Am J Kidney Dis 2004; 43: 90–102
7. Chen TW, Huang T-P, Liu M-C et al. The removal index for evaluation
of dialysis. Perit Dial Int 1996; 16: 128–134
8. Keshaviah P, Star RA. A new approach to dialysis quantification: an
adequacy index based on solute removal. Semin Dial 1994; 7: 85–90
9. Keshaviah P. The solute removal index—a unified basis for comparing
disparate therapies. Perit Dial Int 1995; 15: 101–104
10. Cheng YL, Wong AKW, Choi KS et al. Comparison of methods to
estimate equilibrated Kt/V (eKt/V). J Am Soc Nephrol 1997; 8: 279A
Impact of dialysis modality on skin colour
11. Waniewski J, Lindholm B. Fractional solute removal and KT/V in
different modalities of renal replacement therapy. Blood Purif 2004;
22: 367–376
12. Casino FG, Lopez T. The equivalent renal urea clearance: a new
parameter to assess dialysis dose. Nephrol Dial Transplant 1996; 11:
1574–1581
13. Gotch FA. The current place of urea kinetic modelling with respect to
different dialysis modalities. Nephrol Dial Transplant 1998; 13(Suppl
6): 10–14
14. Depner TA, Bhat A. Quantifying daily hemodialysis. Semin Dial 2004;
17: 79–84
15. Suri R, Depner TA, Blake PG et al. Adequacy of quotidian hemodialysis. Am J Kidney Dis 2003; 42(Suppl 1): S42–S48
16. Tattersall J, Martin-Malo A, Pedrini L et al. EBPG guideline on
dialysis strategies. Nephrol Dial Transplant 2007; 22(Suppl 2):
ii5–ii21
17. Hemodialysis Adequacy 2006 Work Group. Clinical practice guidelines for hemodialysis adequacy, update 2006. Am J Kidney Dis 2006;
48(Suppl 1): S2–S90
18. Tattersall JE, DeTakats D, Chamney P et al. The post-hemodialysis
rebound: predicting and quantifying its effect on Kt/V. Kidney Int
1996; 50: 2094–2102
2803
19. Farrell PC, Gotch FA. Dialysis therapy guided by kinetic modelling:
applications of a variable-volume single-pool model of urea kinetics.
Second Australasian Conference on Heat and Mass Transfer, The
University of Sydney, Sydney, 1977, 29–37
20. Gotch FA. Kinetic modeling in hemodialysis. In: Nissenson AR, Fine
RN, Gentile DE (eds). Clinical Dialysis, 3rd edn. Norwalk, CT: Appleton & Lange, 1995, 156–188
21. Daugirdas JT, Blake PG, Ing TS. Table A-1. Estimating dialyzer blood
water clearance from KoA, Qb and Qd. Handbook of Dialysis, 3rd edn.
Philadelphia, PA: Lippincott Williams & Wilkins, 2001, 674
22. Depner TA, Greene T, Gotch FA et al. Imprecision of the hemodialysis
dose when measured directly from urea removal. Kidney Int 1999; 55:
635–647
23. Kjellstrand CM, Ing TS. Why daily hemodialysis is better: decreased
unphysiology. Semin Dial 1999; 12: 472–477
24. Sargent JA. Control of dialysis by a single pool model: the National Cooperative Dialysis Study. Kidney Int 1983; 23(Suppl 13):
S19–S25
25. Borah MF, Schoenfeld PY, Gotch FA et al. Nitrogen balance during
intermittent dialysis therapy for uremia. Kidney Int 1978; 14: 491–500
26. Gotch F. Is Kt/V urea a satisfactory measure for dosing the newer
dialysis schedules? Semin Dial 2001; 14: 15–17
Received for publication: 18.4.08; Accepted in revised form: 31.1.09
Nephrol Dial Transplant (2009) 24: 2803–2809
doi: 10.1093/ndt/gfp143
Advance Access publication 2 April 2009
The impact of dialysis modality on skin hyperpigmentation
in haemodialysis patients
Sung Jin Moon∗ , Dong Ki Kim∗ , Jae Hyun Chang, Chan Ho Kim, Hyun Wook Kim, Sun Young Park,
Seung Hyeok Han, Jung Eun Lee, Tae-Hyun Yoo, Dae Suk Han and Shin-Wook Kang
Department of Internal Medicine, College of Medicine, Brain Korea 21 for Medical Science, Yonsei University, Seoul, Korea
Correspondence and offprint requests to: Shin-Wook Kang; E-mail: [email protected]
∗
Both the authors contributed equally to this work.
Abstract
Background. Skin hyperpigmentation in end-stage renal
disease (ESRD) patients has been attributed to the accumulation of middle-molecular-weight (MMW) substances.
Although an MMW mechanism suggests that hyperpigmentation may be improved by high-flux haemodialysis (HFHD) and haemodiafiltration (HDF), this possibility has not
been explored. In the present study, we investigated the impact of different dialysis modalities on skin colour in HD
patients.
Methods. Eighty-two ESRD patients on HD were divided
into low-flux HD (LF-HD), HF-HD and HDF groups. The
melanin index (MI) and erythema index (EI) of the abdomen and the flexor side of the forearm (non-sun-exposed
areas) and the forehead (sun-exposed area) were determined
by using a narrow-band reflectance spectrophotometer at
baseline and after 12 months.
Results. Even though absolute values of baseline and
follow-up MI and EI of the three sites were comparable
among the three groups, forehead MI and EI were significantly decreased after 12 months in the HDF group
(P < 0.05). In addition, the change in forehead MI was
significantly greater in the HDF than in the LF-HD group
(−1.0 ± 2.4% versus 0.3 ± 1.6%, P < 0.05). Moreover, β2 microglobulin reduction rates were negatively correlated
with both changes in forehead MI (P < 0.01) and EI
(P < 0.05).
Conclusions. Skin colour of sun-exposed areas was significantly decreased in ESRD patients receiving HDF therapy,
suggesting that enhanced removal of MMW substances by
convection may prevent or reduce hyperpigmentation in HD
patients.
Keywords: β2 -microglobulin; haemodiafiltration; hyperpigmentation;
low-flux haemodialysis; spectrophotometer
C The Author [2009]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
For Permissions, please e-mail: [email protected]
Nephrol Dial Transplant (2012) 27: 777–784
doi: 10.1093/ndt/gfr383
Advance Access publication 1 July 2011
Equivalent continuous clearances EKR and stdK in incremental
haemodialysis
Aarne Vartia
Savonlinna Central Hospital, Dialysis Unit, Savonlinna, Finland
Correspondence and offprint requests to: Aarne Vartia; E-mail: [email protected]
The renal excretion profile of uraemic solutes is different from that in dialysis. Diuresis helps in managing fluid
overload with all of its consequences. RRF lowers predialysis concentrations and reduces the required dialysis
dose, diminishing the concentration and volume fluctuations
and inconvenience of the treatment.
In the CANUSA study [2], the differences in CAPD
outcome were due to differences in RRF [3]. In haemodialysis, RRF correlates positively to outcome [1, 4–10],
but early initiation of dialysis [11–23] and extreme attempts to preserve RRF [24–26] are not unequivocally
beneficial.
Incremental dialysis [9, 27–32] is a concept of adjusting
dialysis dose according to RRF. It was used in 16.5% of
patients in the IDEAL study [20]. The most straightforward
application of incremental dialysis is a treatment frequency
<3 /wk used for example by Casino and Lopez [28].
RRF is in effect 168 h per week and may contribute
significantly to the total solute removal but only minimally
to session Kt/V. Renal function is the reference to which
dialysis should be compared. Kt/V, where ‘K’ is defined
as dialyser urea clearance, is a measure of a single session
and does not permit comparison of different intermittent
and continuous treatments and renal function.
Equivalent renal urea clearance (EKR, Casino and Lopez
[28]) and standard urea clearance (stdK, Gotch [33, 34])
take the treatment frequency and RRF into account and
were intended to be used in comparing dialysis doses in
different schedules and to continuous dialysis and renal
function. EKR and stdK are based on the definition of
clearance (K):
Keywords: computer simulation; EKR; incremental dialysis; residual
renal function; stdKt/V
Introduction
Patients having residual renal function (RRF) are not a
marginal group in the haemodialysis population. In a Dutch
study, only 25.5% were anuric at 12 months from beginning
of dialysis and 58.1% at 36 months [1].
K ¼ E=C:
ð1Þ
In steady state, the excretion rate equals the generation
rate: E ¼ G, so
K ¼ G=C
ð2Þ
In EKR, C is the time-averaged concentration (TAC) and
in stdK, the average pre-dialysis concentration (PAC). stdK
The Author 2011. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
For Permissions, please e-mail: [email protected]
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Abstract
Background. Many haemodialysis patients have residual
renal function (RRF), which as such is insufficient to maintain satisfactory quality of life but reduces the demands
of treatment and improves outcomes. In incremental dialysis, the dose is adjusted according to RRF, but how should
it be done?
Methods. Urea generation rate (G) and distribution volume
(V) were determined by the double-pool urea kinetic model
in 225 haemodialysis sessions of 30 patients. The effect
of different degrees of RRF on equivalent renal urea clearance (EKR), standard urea clearance (stdK) and urea concentrations and required treatment times to achieve the
HEMO study standard dose equivalent EKR and stdK
targets were studied by computer simulations.
Results. Ignoring RRF leads to underestimation of EKR,
stdK, urea generation rate and protein equivalent of nitrogen appearance. Both EKR and stdK increase linearly with
renal urea clearance (Kr). The HEMO standard dose equivalent EKRc is 13.8 mL/min/40 L and stdK/V 2.29 /wk
(9.1 mL/min/40 L). The required treatment time to achieve
the HEMO-equivalent targets has an almost linear inverse
relationship to Kr. If the HEMO standard dose equivalent
EKR or stdK is used as the target, RRF may replace several
hours of weekly dialysis treatment time. stdK appreciates
RRF more than EKR.
Conclusions. RRF is included in the original EKR and
stdK concepts. EKR and stdK—determined by kinetic
modelling—are promising measures of adequacy in incremental dialysis.
778
A. Vartia
is normalized by dividing the value of equation (2) by the
distribution volume V and expressed usually as weekly
stdKt/V. Dividing EKR by V yields a variable denoted
here as stdEKR. G, V, TAC and PAC can be determined
by kinetic modelling.
EKR ¼ G=TAC;
ð3Þ
stdEKR ¼ EKR=V
ð4Þ
weekly stdEKR ¼ EKR3t=V
ð5Þ
stdK ¼ G=PAC;
ð6Þ
stdK=V ¼ stdK=V ¼ G=PAC=V ;
ð7Þ
weekly stdKt=V ¼ stdK3t=V :
ð8Þ
EKRc ðmL=min=40 LÞ ¼ 3:973stdEKRð=wkÞ:
ð9Þ
The total fractional solute removal rate (tFURR) of urea
is defined here as the amount removed by dialysis and the
kidneys during a time unit divided by the average predialysis amount in the body:
tFURR ¼ E=ðPAC3V Þ:
ð10Þ
As seen from equations (7) and (10), in a symmetric
schedule tFURR ¼ stdK/V, if E ¼ G. The most practical
unit is /wk. tFURR can be divided into renal fractional
solute removal rate (rFURR) and dialysis fractional solute
removal rate (dFURR) components without dialysate collection. The sum of the urea reduction ratios (URR) of 1
week’s sessions is a rough approximate of dFURR.
In the double-pool model, it is not obvious, which concentration should be used as TAC and PAC: whole body
water, external pool water or plasma concentration. It is a
convention, which has not yet been done. In fractional
solute removal rate, the whole body water concentration
without converting to plasma concentration must be used
and tFURR 6¼ stdK/V.
The European Best Practice Guidelines recommend
EKR [36] or Solute Removal Index [37] for measuring
the dialysis dose in incremental dialysis. Casino and Lopez
[28] have created a rough linear regression equation between EKRc and spKt/V, used for example in ref. [38].
Materials and methods
A detailed description of the abbreviations, symbols, definitions and equations is presented in ref. [44].
The data have been gathered by a dialysis information system in the
routine care of haemodialysis patients and analysed retrospectively. No
randomization, control group or study protocol has been used.
Dialysis sessions
The analysis is based on 225 urea kinetic modelling sessions with measurable
interdialysis urine volume (Table 1). All the patients were white Europeans.
Dialyser clearances
Dialyser clearances are based on 964 in vivo blood side clearance
measurements. From these, the average blood water KoA is calculated
for each dialyser model. The actual clearance of each session in this
study is calculated from the actual blood and dialysate flow and the
dialyser KoA. In the tables and figures, the ‘dialyser blood water clearance’ means the total (diffusive 1 convective) clearance used in
calculations.
Double-pool UKM
Urea kinetic modelling with three blood samples and interdialysis urine
collection was done routinely once per month as suggested in the European [37] and American [45] guidelines. Post-dialysis blood samples were
taken at the termination of the session with the KDOQI slow-blood-flow
Table 1. The current material
Number of sessions
Females
Age
Height
Post-dialysis weight
BMI
Total body water
(Watson)
Post-dialysis urea
distribution volume
Urea generation rate
nPNA
Diuresis
Renal blood water
urea clearance
Renal fractional
urea clearancea
Unit
Mean
SD
Min
Max
%
Years
cm
kg
kg/m2
L
225
42.7
64.9
167
80.5
28.8
39.4
16.7
10
18.5
5.7
8.2
17.1
151
48.8
18.8
27.0
91.0
187
133.8
44.7
60.8
L
32.6
7.2
14.4
52.3
lmol/min
g/kg/day
L/day
mL/min
211
1.15
0.68
1.98
77
0.27
0.45
1.27
68
0.62
0.01
0.03
494
2.02
2.30
6.32
/wk
0.60
0.35
0.01
1.72
a
Renal fractional urea clearance (rFC) is renal urea clearance (Kr) divided
by urea distribution volume (V) with appropriate unit conversions, sometimes called as ‘‘weekly renal Kt/V’’. nPNA, normalized Protein equivalent
of Nitrogen Appearance.
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
In the above equations, t is the length of a week. The
most practical unit of stdEKR and stdK/V is /wk; weekly
stdEKR and weekly stdKt/V are dimensionless. stdEKR is
always higher than stdK/V because PAC > TAC. PAC has
also been called peak average concentration, too [35]. In a
symmetric schedule, the peak concentration is equal to the
average pre-dialysis concentration. In continuous treatment,
TAC, PAC and peak concentrations are equal.
Corrected EKR (EKRc) is stdEKR multiplied by a ‘normal’ distribution volume of 40 L with appropriate unit
conversions [28]. The proposed unit of EKRc is mL/
min/40 L. It is comparable to a clearance expressed in
mL/min/1.73m2, but with a different scaling factor.
The Leypoldt’s weekly stdKt/V formula [39, 40], as expressed and recommended in the 2006 DOQI guidelines
[41], ignores RRF leading to underestimation of weekly
stdKt/V if the patient has remarkable RRF. Recently, an
improved weekly stdKt/V equation taking ultrafiltration
(UF) and RRF into account has been published [42] and
used in the Frequent Hemodialysis Network (FHN) Trial
[43].
The a priori assumption is that renal function is not
worse than dialysis with equal urea clearance, but the
problem is how to measure urea clearances in intermittent
dialysis. This study compares EKR and stdK as dialysis
dose measures when RRF is present.
Equivalent continuous clearances EKR and stdK
corresponds to EKRc 13.8 mL/min/40 L and stdK/V to
9.1 mL/min/40 L.
In the subsequent analysis, only the 225 sessions with
measurable RRF were included. The mean renal urea
clearance was 1.98 mL/min (0.03–6.32).
The data in Figures 1–6 and in Tables 2–3 are derived
from simulations as described in the Materials and methods
section. In all figures, the treatment frequency is 3 3 /wk
and dialyser blood water clearance 187 mL/min to achieve
HEMO eKt/V 1.20 in 4 h. In the figures G, V and weekly
UF are the average values of the study material (211 lmol/
min, 32.6 L and 6.72 L/wk, Tables 1 and 2).
Effect of Kr on measures of RRF and dialysis dose
stdEKR increases in parallel with renal fractional clearance
(rFC ¼ Kr/V), stdK/V in parallel with rFURR (Figure 1).
HEMO-equivalent stdEKR and stdK/V
In the HEMO study [51], standard dose group average eKt/V was 1.16.
To get a safety margin for anuric patients, and due to the bias of the
HEMO modification of the Daugirdas rate equation [52], stdEKR and
stdK/V values corresponding to eKt/V 1.20 in a conventional 4-h dialysis
given three times per week (3 3 4 h/wk) schedule were calculated from
619 modelling sessions (including the 225 of the proper study) as
follows:
Single-pool urea distribution volume V1p was calculated for each session with the classic single-pool variable volume urea kinetic model, using
Kr determined by the double-pool method. Kd was solved from the Daugirdas eKt/V rate equation:
Kd ¼ ðeKt=V aÞ3V 1p=ðtd bÞ;
and 1.20 assigned to eKt/V, 240 min to td and Kd calculated. Dialysis
treatment 3 3 4 h/wk was simulated with the double-pool model for each
session with this Kd and Kr ¼ 0. stdEKR and stdK/V were calculated. In
the HEMO study and in this analysis, a ¼ 0 and b ¼ 24 min. No
distinction is made between A V and V V blood access.
Fig. 1. Effect of Kr on measures of RRF and dialysis dose. Standard
dialysis (3 3 4 h/wk, Kd 187 mL/min, HEMO eKt/V 1.20, UF 2.24 L).
Simulations
The effect of RRF on measures of dialysis dose was studied by simulations based on the double-pool model with the patient-dependent values G and V from the modelling session and varying Kr and treatment
parameters, assuming that dialysis has no effect on urea generation and
renal urea clearance. The simulations give C0, Ct, TAC, eKt/V, EKR and
stdK. With simple computing techniques, one may search for appropriate
values of dialysis parameters to achieve a specific stdEKR or stdK/V
target.
Statistical methods
Microsoft Excel 2002 software was used in calculating minimum and
maximum values and standard deviations and in creating the graphs.
Results
The HEMO-equivalent values of stdEKR and stdK/V were
3.48 /wk and 2.29 /wk, respectively. The stdEKR value
Fig. 2. Dependence of required weekly treatment time on RRF. Frequency 3 3 /wk, Kd 187 mL/min.
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
technique. Originally, classic single-pool variable volume urea kinetic
model [46–48] was used, but the data permitted three blood sample
double-pool calculations for this retrospective analysis. Plasma concentrations were converted to plasma water concentrations before calculations
and back to plasma concentrations in the tables and figures, but renal and
dialyser clearances are expressed as blood water clearances. Plasma clearances, used commonly in renal function measurements, are 7.5% and
whole blood clearances, used as dialyser efficiency measures, 16.3%
higher.
Runge-Kutta numeric integration procedure—modified from the SoluteSolver programme code (version 1.97, [49])—was used in the double-pool
model. The constants were the same as in Solute-Solver: blood water ¼
0.86 3 blood volume; plasma water ¼ 0.93 3 plasma volume; internal
compartment volume ¼ 2/3 of total post-dialysis volume does not change
during dialysis cycle; external compartment post-dialysis volume ¼ 1/3 of
total post-dialysis volume; intercompartment clearance (Kc, L/min) =
0.016 (/min) 3 total postdialysis volume (L).
Renal blood water urea clearance (Kr) was determined by an extra
iteration and double-pool eKt/V calculated as in Solute-Solver programme
code.
For best comparability to earlier studies, external pool water concentrations converted to plasma concentrations were used in calculating
stdEKR and stdK/V. The difference between whole body and external
pool pre-dialysis concentrations is small. Fortunately, all TACs (external
and internal pool and whole body water) are equal.
Time-averaged concentration (TAC) and average pre-dialysis concentration (PAC), needed in calculating EKR and stdK, were determined after
equalizing the schedule to a symmetric one as described in ref. [44], using
the double-pool model. Then, the analysis could be concerned with only
one dialysis cycle. Time-averaged deviation (TAD) was calculated according to Lopot and Válek [50].
779
780
A. Vartia
Fig. 5. Dependence of TAD on RRF. Frequency 3 3 /wk, Kd 187 mL/
min, dose adjusted by treatment time.
Fig. 4. Dependence of TAC on RRF. Frequency 3 3 /wk, Kd 187 mL/
min, dose adjusted by treatment time.
Fig. 6. Renal fraction of total urea excretion. Frequency 33 /wk, Kd 187
mL/min, dose adjusted by treatment time.
Effect of RRF on the required treatment time
In Tables 2 and 3, the results are calculated individually
from td, Kd, G, V and UF of each session and the means
of these calculations are presented. The true double-pool
eKt/V is shown. It is ~0.05 less than that calculated by the
modified Daugirdas rate equation used in the HEMO study.
Weekly eKt/V is eKt/V multiplied by treatment frequency
individually for each session.
Ignoring RRF does not affect V or eKt/V but lowers considerably G, normalized Protein equivalent of Nitrogen Appearance, stdEKR and stdK/V. RRF lowers concentrations
and increases stdEKR and stdK/V (Columns 5 and 3 in
Table 2). The treatment time had to be increased by 56 or
123 min per dialysis session to achieve the actual stdEKR
or stdK/V, respectively, without RRF.
Because the actual stdEKR and stdK/V values (Table 2)
were substantially greater than the HEMO-equivalent stand-
ard dose, simulations with lower dialysis intensity were
done to confirm the effect of RRF on the required dialysis
time. To achieve the HEMO standard dose equivalent
targets, 64 or 123 min more treatment time per session were
needed if the patients had had no RRF (Table 3). Of course,
in most instances, it had been possible to increase Kd to
achieve the target in a shorter time. In this material, the
average renal urea clearance 1.98 mL/min corresponds to
0.25–0.36 units of eKt/V.
The average renal urea removal rate is lower with higher
dialysis intensity (Column 3 in Table 2 and Columns 3 and
5 in Table 3). Total urea removal rate equals generation
rate.
In Figures 2–6, the dialysis dose is varied in an incremental fashion by adjusting the treatment time to achieve
the HEMO standard dose equivalent stdEKR and stdK/V
targets.
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
Fig. 3. Dependence of pre-dialysis urea concentration C0 on RRF. Frequency 3 3 /wk, Kd 187 mL/min, dose adjusted by treatment time.
Equivalent continuous clearances EKR and stdK
781
a
Table 2. Required treatment time to achieve the actual stdEKR and stdK/V without RRF
3
Actual
4
Ignored
5
Without
6
stdEKR
7
stdK/V
L
lmol/min
g/kg/day
mL/min
mL/min
/wk
min
h
L
L
mmol/L
mmol/L
mmol/L
mmol/L
/session
/session
/wk
/wk
/wk
/wk
lmol/min
lmol/min
lmol/min
%
32.6
211
1.15
1.98
199
2.97
285
14.1
2.26
6.72
20.8
5.2
13.5
3.9
0.75
1.51
4.50
4.73
2.95
2.76
30
181
211
13.6
32.8
181
1.02
0.0
199
2.97
285
14.1
2.26
6.72
20.9
5.2
13.4
3.9
0.75
1.51
4.48
4.14
2.54
2.38
0
181
181
0.0
32.6
211
1.15
0.0
199
2.97
285
14.1
2.26
6.72
24.4
6.1
15.6
4.6
0.75
1.52
4.50
4.16
2.55
2.38
0
211
211
0.0
32.6
211
1.15
0.0
199
2.97
341
16.8
2.26
6.72
22.2
4.5
13.5
4.4
0.80
1.83
5.41
4.73
2.76
2.59
0
211
211
0.0
32.6
211
1.15
0.0
199
2.97
408
19.9
2.26
6.72
20.8
3.5
12.1
4.3
0.83
2.19
6.46
5.27
2.95
2.76
0
211
211
0.0
a
The mean actual values of the material are shown in Column 3. Column 4 shows the values calculated by ignoring RRF. Column 5 shows the values if
the patients really had had no RRF and they had been dialysed as they actually were. Columns 6 and 7 show the treatment times required to achieve the
actual stdEKR and stdK/V with equal dialyser clearances but without RRF. The most important values are in bold. nPNA, normalized Protein equivalent
of Nitrogen Appearance.
Table 3. Required treatment time to achieve the HEMO-equivalent stdEKR and stdK/V without RRF. In Columns 3 and 5, the dialyser clearance has
been adjusted to achieve the HEMO standard dose equivalent targets in 3 3 4 h/wk in the current material; in Columns 4 and 6, the treatment duration is
adjusted to achieve the same target with equal dialyser clearance but without RRF
Renal blood water urea clearance
Dialyser blood water urea clearance
Dialysis frequency
Dialysis time
Weekly dialysis time
Ultrafiltration volume
Weekly ultrafiltration volume
Pre-dialysis plasma concentration
Post-dialysis plasma concentration
Time-averaged plasma concentration
Time-averaged deviation
Urea reduction ratio
Double-pool eKt/V
Weekly double-pool eKt/V
stdEKR
stdK/V
Total fractional urea removal rate
Renal urea removal rate
Dialysis urea removal rate
Total urea removal rate
Renal fraction of urea removal
3
HEMO stdEKR
4
5
HEMO stdK/V
6
Unit
with RRF
without
with RRF
without
mL/min
mL/min
/wk
min
h
L
L
mmol/L
mmol/L
mmol/L
mmol/L
/session
/session
/wk
/wk
/wk
/wk
lmol/min
lmol/min
lmol/min
%
1.98
146
3.00
240
12.0
2.24
6.72
24.7
10.1
18.1
3.7
0.59
0.90
2.69
3.48
2.47
2.30
40
171
211
18.1
0.0
146
3.00
304
15.2
2.24
6.72
26.5
8.9
18.1
4.4
0.66
1.14
3.42
3.48
2.30
2.15
0
211
211
0.0
1.98
124
3.00
240
12.0
2.24
6.72
26.7
12.7
20.4
3.5
0.53
0.75
2.26
3.11
2.29
2.14
47
164
211
21.1
0.0
124
3.00
363
18.2
2.24
6.72
26.7
9.6
18.5
4.3
0.64
1.11
3.33
3.42
2.29
2.14
0
211
211
0.0
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
Post-dialysis urea distribution volume
Urea generation rate
nPNA
Renal blood water urea clearance
Dialyser blood water urea clearance
Dialysis frequency
Dialysis time
Weekly dialysis time
Ultrafiltration volume
Weekly ultrafiltration volume
Pre-dialysis plasma concentration
Post-dialysis plasma concentration
Time-averaged plasma concentration
Time-averaged deviation
URR
Double-pool eKt/V
Weekly double-pool eKt/V
stdEKR
stdK/V
Total fractional urea removal rate
Renal urea removal rate
Dialysis urea removal rate
Total urea removal rate
Renal fraction of urea removal
Unit
782
In incremental dialysis, with Kr ¼ 4 mL/min, the target
stdK/V is achieved in one half of the time required without RRF.
Somewhat longer treatment time is required to achieve the
stdEKR target. In both cases, the required treatment time has
an almost linear inverse relationship to Kr (Figure 2).
Effect of RRF on urea concentrations
With increasing Kr, dialysing to a constant stdEKR results in
decreasing pre-dialysis concentration C0 (Figure 3).
Dialysing to a constant stdK/V results in increasing TAC
with increasing Kr (Figure 4). TAD reflects the fluctuation of concentrations. It decreases when Kr increases with
constant stdEKR or stdK/V (Figure 5).
Contribution of RRF to urea excretion
Discussion
The current analysis is based on the urea kinetic model.
One of the parameters in the model is the renal urea clearance (Kr), which is lower than the glomerular filtration rate.
European guidelines [36, 37] suggest glomerular filtration
rate as the measure of RRF of dialysis patients, American
[41] the urea clearance.
The average kinetic urea distribution volume 32.6 L is
17.5% lower than the anthropometric total body water estimate, only 40% of body mass, but the patients were on
the average overweight [body mass index (BMI) 28.8 kg/
m2]. Daugirdas et al. [53] have observed volume differences of equal magnitude in the HEMO material, where
BMI was lower (25.7 kg/m2) and kinetically determined
volume was 43–44% of body weight.
The HEMO standard dose equivalent stdEKR and stdK/
V values calculated by the double-pool model (3.48 /wk and
2.29 /wk, respectively) are higher than those reported earlier
using the single-pool model with equilibrated post-dialysis
concentrations (3.34 /wk and 2.23 /wk) [44].
According to urea kinetics, RRF may replace several
hours of weekly dialysis treatment time in a conventional
three times per week schedule, if HEMO-equivalent
stdEKR and stdK/V values are used as targets. Each mL/
min of renal urea clearance corresponds to about 30–60
min of session time in a standard 3 3 /wk schedule with
HEMO-equivalent intensity. Each weekly dialysis hour
replaces ~0.7 mL/min of missing renal urea clearance.
Other uraemic solutes may behave differently.
Originally Casino and Lopez [28] held EKRc 11 mL/
min/40 L (stdEKR 2.77 /wk) and Gotch [29, 33] stdK/V
2.0 /wk (7.8 mL/min/40 L) as an adequate dose. Later
higher targets were proposed. The HEMO standard dose
equivalent stdK/V 2.29 /wk is equal to 9.1 mL/min/40 L
corresponding to an acceptable urea clearance without dialysis. Patients with renal urea clearance of 13.8 mL/min/
40 L (stdEKR 3.48 /wk) may have months or even years
of satisfactory life left before they begin to benefit from
dialysis. Empirically, the optimal stdEKR and stdK/V values are in conventional haemodialysis considerably higher
than in CAPD (HEMO [51], ADEMEX [54]). This discrepancy may have several explanations:
(1) the lower TAC in intermittent treatment compensates
the drawbacks of concentration and volume fluctuations;
(2) the relationship between toxicity and concentration is
not linear (the peak concentration hypothesis [55]) and
(3) the excretion profile of uraemic solutes is different in
renal function and CAPD and haemodialysis, i.e. urea
is not a good marker solute.
These and other possible factors have been managed
in stdK by using a different denominator in the clearance
equation (2), making stdK therapeutically ‘more equivalent’
than EKR, which is a ‘mathematically correct’ average
clearance.
RRF is inherently included in stdEKR and stdK/V calculated by the urea kinetic model. RRF lowers especially
the pre-dialysis concentrations (denominator in equation
(6)) and is included in the UKM formula of G (numerator
in equations (3) and (6); Table 2). Using stdK/V as the
dosing guide in incremental dialysis results in shorter
treatment times, lower Kt/V, lower TAD and higher urea
concentrations than using EKR (Figures 2–4 and Table 3).
When the dialysis intensity increases, the renal excretion of urea decreases (Table 3, Columns 5 and 3) and
when RRF increases, elimination by dialysis decreases
(Figure 6). In intermittent dialysis, the average rFURR
(/wk) is lower than the renal fractional urea clearance
(rFC ¼ Kr/V, /wk) (Figure 1, [42]). dFURR and rFURR
depend on each other because both RRF and dialysis
affect pre-dialysis concentrations (the denominator) and
compete for excretion (the numerator). Total stdK/V cannot be calculated by adding rFC to stdK/V calculated with
the Leypoldt formula [41] (Figure 1).
Residual renal urea clearance ~4 mL/min/40 L may be
the threshold above which concrete short-term benefits
may be obtained from incremental dialysis, in the form
of a twice per week treatment schedule. It is not far below
the threshold above which dialysis is usually not useful.
In only 5.5% of all UKM sessions in one centre during
3 years, Kr was >4 mL/min (Vartia A, unpublished). The
HEMO standard dose equivalent EKR was not achieved
in a 2 3 /wk schedule with an average session Kt/V 1.86
[56]. But many patients appreciate shortening of the session time, too.
In conclusion, if we use systematically stdEKR and stdK/V
as adequacy measures, RRF and treatment frequency will
automatically be taken into account. Urea kinetic modelling
and a computer are needed in creating the prescriptions.
There is in the literature very scanty information about
the correlation of stdEKR or stdK/V to outcome [38, 43]
and no studies comparing outcomes in incremental and
full-dose approaches. In the FHN trial [43], the average
stdK/V was considerably higher in the frequent haemodialysis group than in the conventional treatment group (3.60
versus 2.57 /wk), but it is difficult to estimate whether the
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
Figure 6 presents the fraction (%) of total urea elimination
excreted by the kidneys. With Kr ¼ 4 mL/min, using the
HEMO-equivalent stdK/V as target, almost one half of
the total urea excretion takes place through the kidneys.
Dialysis and the kidneys interfere with each other and compete for solutes.
A. Vartia
Equivalent continuous clearances EKR and stdK
better outcome was due to the lower concentrations (higher
‘dose’), smaller fluctuation of concentrations and volume,
longer weekly treatment time or other factors. Has there
been any difference in outcomes, if stdK/V had been equal
in both groups? There is no empiric proof showing that
equal stdEKR or stdK/V results in equal outcomes in different schedules and with different degrees of RRF, i.e. that
they are really universal measures of dialysis adequacy.
There is also no data showing which is better as the dosing
guide (with different target values), stdEKR or stdK/V, i.e.
which correlates more tightly to outcome. stdK/V is more
sensitive to RRF and treatment frequency [44, 57] than
stdEKR. It is based on the hypothesis that pre-dialysis or
peak urea concentrations are important. Using stdK/V as
target may lead to high time-averaged urea concentrations
and short treatment times, which may hamper water,
middle molecule and protein-bound toxin removal. If we
apply incremental dialysis, it is important to measure RRF
frequently because it may deteriorate unexpectedly.
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Received for publication: 12.2.11; Accepted in revised form: 8.6.11
Nephrol Dial Transplant (2012) 27: 784–790
doi: 10.1093/ndt/gfr384
Advance Access publication 5 July 2011
Cinacalcet treatment and serum FGF23 levels in haemodialysis patients
with secondary hyperparathyroidism
Masahiro Koizumi1,2, Hirotaka Komaba1,2, Shohei Nakanishi2, Akira Fujimori3 and
Masafumi Fukagawa1,2
1
Division of Nephrology, Endocrinology and Metabolism, Tokai University School of Medicine, Isehara, Japan, 2Division of
Nephrology and Kidney Center, Kobe University School of Medicine, Kobe, Japan, 3Chibune Kidney and Dialysis Clinic, Osaka, Japan
and 4Division of Blood Purification and Kidney Center, Konan Hospital, Kobe, Japan
Correspondence and offprint requests to: Masafumi Fukagawa; E-mail: [email protected]
Abstract
Background. Elevated fibroblast growth factor 23 (FGF23)
is associated with adverse clinical outcomes and development of secondary hyperparathyroidism (SHPT) refractory
to active vitamin D. Cinacalcet hydrochloride is effective in
treating SHPT, but little is known as to whether treatment
with cinacalcet alters these levels and whether pretreatment
FGF23 levels predict response to this therapy.
Methods. We measured serum full-length FGF23 levels in
55 haemodialysis patients, who participated and completed
the 52-week, multicentre, open-label single-arm trial that
examined the effectiveness of cinacalcet for treating SHPT.
The Author 2011. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
For Permissions, please e-mail: [email protected]
Downloaded from http://ndt.oxfordjournals.org/ by guest on February 28, 2012
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798–809
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600
500
400
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TFTTJPO
ॷ ॶ ॗ 300
200
ॷ ॶ æ 100
ॗ 0
0
20
40
60
80
ज़ -
Females
Males
Linear (females)
Linear (males)
'ĶĴłĿIJ ौ WFSTVT ज़
TUE &,3 BOE TUE ॐज़ NFBO WBMVFT DPSSFTQPOEJOH UP
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50
50
ॷ æॶ 45
ॗ 40
40
35
35
30
30
TAC (mmol/L)
TAC (mmol/L)
45
25
20
20
15
10
10
ॷ ॶ ॗ 25
15
5
ॷ ॶ ॷ ॶ ॗ 5
ॗ 0
0
0
20
40
60
0
80
100
300
400
500
600
ौ ঴NPMNJO
ज़ -
Linear (females)
Linear (males)
Females
Males
200
Linear (females)
Linear (males)
Females
Males
B
C
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800
800
700
700
600
600
ॗ 500
ॗ ॲॣ NJO
ॲॣ NJO
ॷ ॶ æ ॷ ॶ 500
400
300
400
300
200
200
ॷ ॶ æ 100
ॷ ॶ æ 100
ॗ 0
ॗ 0
0
20
40
60
80
0
100
ज़ -
Linear (females)
Linear (males)
Females
Males
B
Females
Males
200
300
400
500
600
ौ ঴NPMNJO
Linear (females)
Linear (males)
C
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20
10
9
16
8
12
stdEKR (/wk)
TAC (mmol/L)
7
8
6
5
4
3
4
2
1
0
0
100
200
300
400
500
600
0
0
100
ौ ঴NPMNJO
Females
Males
200
300
ौ ঴NPMNJO
400
500
600
Females
Males
B
C
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QQ o Original Paper
Received: April 8, 2014
Accepted: June 18, 2014
Published online: October 2, 2014
Blood Purif 2014;38:62–67
DOI: 10.1159/000365347
Adjusting Hemodialysis Dose for
Protein Catabolic Rate
Aarne J. Vartia Dialysis Unit, Savonlinna Central Hospital, Savonlinna, Finland
Abstract
Background: Patients dialyzed with equal eKt/V may have
huge variations in their urea concentrations. Methods: Urea
generation rate, distribution volume and renal clearance
were determined in 205 hemodialysis sessions of 33 patients
with double pool urea kinetic modeling using dialyzer clearance from online monitoring. From these data, optimized
prescriptions were computed. Results: In simulated dialysis
sessions, the HEMO standard-dose equivalent clearance was
not sufficient to keep time-averaged concentration (TAC)
and average predialysis concentration (PAC) of urea below
the defined upper limits (20 and 30 mmol/l), if normalized
protein catabolic rate (nPCR) was greater than 1.3 g/kg/day.
Protein catabolic rate was taken into account in the optimized prescription by cutting high urea concentrations.
Conclusions: If patients having high urea concentrations
with conventional clearance will benefit from higher dialysis
dose – an unconfirmed hypothesis – this approach helps in
identifying those who need more than three sessions per
© 2014 S. Karger AG, Basel
week.
© 2014 S. Karger AG, Basel
0253–5068/14/0381–0062$39.50/0
E-Mail [email protected]
www.karger.com/bpu
Introduction
The therapeutic effect of dialysis is based mainly on
removing water and solutes accumulating in renal insufficiency. Urea is used as a marker; concentrations of
many other, possibly more toxic substances are not routinely measured. In the National Cooperative Dialysis
Study (NCDS), patients with high time-averaged urea
concentrations (TAC) did worse than those with low
ones [1, 2].
In a reanalysis of the NCDS material, Gotch and Sargent [3] demonstrated that the clearance-based variable
Kt/Vurea is a better measure of dialysis dose than urea con-
Glossary: E = Excretion rate; EKR = equivalent renal clearance G/TAC;
eKt/V = equilibrated Kt/V; fr = dialysis frequency; G = generation rate;
K = clearance; Kd = dialyzer clearance; KoA = dialyzer mass area coefficient; Kr = renal clearance; Kt/V = dialyzer clearance × session time,
scaled to distribution volume; LBM = lean body mass; nPCR = PCR
scaled to LBM; PAC = average predialysis concentration, peak average concentration; PCR = protein catabolic rate; Qb = dialyzer blood
flow; Qd = dialysate flow; RRF = residual renal function; spKt/V = single pool Kt/V; stdEKR = EKR scaled to V; stdK = standard clearance G/
PAC; stdK/V = stdK scaled to V; stdKt/V = weekly stdK/V; TAC = timeaveraged concentration; td = dialysis time; UF = ultrafiltration volume; V = total distribution volume (external + internal pool); V1 =
single-pool V; Ve = external pool V; Vi = internal pool V.
Aarne Vartia, MD
Kirkkokatu 9 A 1
FI–57100 Savonlinna (Finland)
E-Mail aarne.vartia @ gmail.com
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Key Words
Adequacy · Dialysis efficiency · Hemodialysis · Kinetic
modeling · Kt/V · Mathematical models · Protein catabolic
rate · Standard Kt/V · Urea clearance
Patients and Dialysis Sessions
Data of 205 dialysis sessions of 33 chronic hemodialysis patients with online clearance monitoring and complete double pool
urea kinetic modeling (UKM) were derived retrospectively from
the information system of a hospital dialysis unit with permission
of the hospital (table 1). The author has been part of the care of all
patients.
The patient’s clinical condition, fluid removal requirement
and eKt/V, stdK/V and laboratory values from the previous sessions were taken into account in defining the prescription. The
patients were encouraged by a dietician to use a diet containing
protein 1.2 g/kg/day, but the actual dietary protein intake was not
controlled.
EKR and stdK as Measures of Dialysis Dose
Equivalent renal urea clearance (EKR, Casino and Lopez) [9]
and stdK (Gotch) [8, 10] take the treatment frequency and residual renal function (RRF) into account and were intended to be used
in comparing dialysis doses in different schedules and to continuous dialysis and renal function [11, 12].
EKR and stdK are based on the definition of clearance (K):
Adjusting Hemodialysis Dose
Age, years
Height, cm
Weight, kg
BSA, m2
BMI, kg/m2
V, l
Kr, ml/min
nPCR, g/kg/day
Avg
stDev
Min
Max
66.3
170
80.6
1.91
28.0
32.6
0.9
1.09
14.6
10
19.1
0.24
5.8
6.5
1.3
0.26
16.3
150
43.4
1.35
16.0
21.8
0.0
0.53
91.4
187
134.5
2.43
44.7
48.7
6.3
1.86
BSA = Body surface area; BMI = body mass index; V = double
pool postdialysis urea distribution volume; Kr = renal blood water
urea clearance; nPCR = normalized protein catabolic rate.
In steady state, the excretion rate equals the generation rate:
E = G, so
K=G/C
(1)
(2)
In EKR, C is the time-averaged concentration (TAC), in stdK,
the average predialysis concentration (peak average concentration, PAC). stdK is scaled to body size by dividing by the urea
distribution volume (V) and expressed as stdK/V (originally as
stdKt/V = weekly stdK/V, a dimensionless variable, where ‘t’ is
fixed to 7 days). Dividing EKR by V yields a variable called here as
stdEKR. The most practical unit of stdEKR and stdK/V is /week.
G, V, TAC and PAC can be determined by kinetic modeling.
stdEKR = (G / TAC) / V
stdK/V = (G / PAC) / V
Materials and Methods
K=E/C
Table 1. Characteristics of 205 dialysis sessions of 33 patients
(3)
(4)
In this article, postdialysis urea distribution volume is used as
V in equations (3) and (4).
In the NCDS study, TAC had tighter association to outcome
than PAC [2]. stdEKR is less sensitive to treatment frequency [11]
and RRF [12] but more sensitive to a poorly spaced schedule than
stdK/V [13].
Urea Kinetic Modeling
Double pool urea kinetic modeling with three blood samples
and interdialysis urine collection was done by calculation methods
modified from the Solute-Solver application [14] and G, V and Kr
determined in each session. The model assumes that the patient
is in stable metabolic steady state, which was not confirmed. The
Borah equation [15] with Sargent’s modification [16] was used in
the nPCR calculation.
The average of several OCM measurements during the session
was used as the dialyzer clearance (Kd) in the UKM equations.
Plasma concentrations were converted to plasma water concentrations before calculations and back to plasma concentrations in the
results.
TAC and PAC were determined after equalizing the schedule
to a symmetric (equally spaced) one by simulation [11], using the
double pool model.
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centration. Since then the doses have increased. The
HEMO study [4] showed that increasing Kt/V above current levels in conventional three times per week schedule
had an insignificant effect on outcome.
Patients with high protein catabolic rate (PCR) have
high urea concentrations when dialyzed with a commonly accepted clearance (Kt/V, stdEKR or stdK/V). In an
unselected hemodialysis population, the variation of predialysis urea concentrations was 6.1-fold [5].
Morton and Singer [6] propose that the dialysis dose
should be normalized to the metabolic rate. Concentrations of several uremic toxins correlate to the protein catabolic rate in hemodialysis patients [7]. Gotch and Sargent [3, 8] recommend spKt/V 0.9–1.0 for patients with a
low urea generation rate (G) and higher for those with a
high G, roughly equal to the numeric value of nPCR in
the 3×/week schedule. This strategy has not been tested
in outcome trials.
In this study, I describe a hemodialysis prescription
model, which resembles the Gotch’s and Sargent’s old
concept, but includes residual renal function (RRF) and
utilizes double pool urea kinetics, variable schedules and
online clearance monitoring (OCM). The dialysis dose
will be increased for patients with a high nPCR. The optimized prescriptions generated with this model are compared to the conventional and HEMO-equivalent ones.
Patient outcomes are not reported.
HEMO-Equivalent stdEKR and stdK/V
In the standard-dose group of the HEMO study [4], the average
eKt/V was 1.16. One-third of the patients had RRF. To get a safety
margin for anuric patients, stdEKR and stdK/V values corresponding to eKt/V 1.20 in a conventional four-hour dialysis given three
times per week (3 × 4 h/week) schedule without residual renal
function (RRF) were calculated for each session as follows:
Single pool urea distribution volume (V1) was calculated with
the classic single pool variable volume urea kinetic model (spvv
UKM), using online Kd and Kr determined by the double pool
method. Then Kd was solved from the Daugirdas eKt/V rate equation [17, 18]:
eKt/V = (Kd * td / V1) – b * (Kd * td / V1) / td + a
Kd = (eKt/V – a) * V1 / (td – b).
(5)
(6)
1.20 was assigned to eKt/V and 240 min to td. In sessions with
arteriovenous blood access, a was 0.03 and b 36 min, with venovenous access 0.02 and 28 min. Dialysis treatment 3 × 4 h/week was
then simulated with the double pool model for each session with
this Kd and Kr = 0. stdEKR and stdK/V were calculated and used
as the minimum (HEMO-equivalent) limits in the optimization
algorithm individually for each session.
Table 2. Optimization criteria
Treatment frequency, week
Treatment time, min
Dialysate flow, ml/min
Blood flow, ml/min
stdEKR, week
stdK/V, week
TAC, mmol/l
PAC, mmol/l
Min
Max
2
240
300
50
3.442
2.352
7
300
800
2871
20.0
30.0
1 Average
value. The blood flow upper limit used in each optimized session was 90% of the patient’s maximum blood flow
during the previous four weeks. 2 Average value. The minimum
stdEKR and stdK/V were defined individually for each session
to correspond to eKt/V 1.2 in a 3 × 4 h/week schedule without
RRF.
Optimization Algorithm
V, G, Kr and weekly fluid removal requirement are the patient
data needed in creating the dialysis prescription. They are derived
from the real actual dialysis sessions. The goal of the optimization
procedure is to generate from each dataset a prescription fulfilling
twelve criteria (table 2).
Qb and td are continuous variables. The frequency values are
2, 3, 3.5 (alternate day), 4, 5, 6 and 7/week and dialysate flow 300,
500 and 800 ml/min.
Prescription generation starts with simulations with minimum
fr, Qb, Qd and td. If more dialysis is needed, Qb is increased first,
then Qd to 500 ml/min, then td, then Qd to the maximum value
and the treatment frequency only as the last means. Weekly UF
volume and the dialyzer (KoA) are held constant within each simulation. RRF (Kr) is taken into account.
A detailed description of the optimization procedure and some
examples can be found in the online supplementary APPENDIX
Online Material (www.karger.com/doi/10.1159/000365347). A
simplified version of the program used in generating the optimized
prescriptions can be downloaded from http://www.verkkomunu
ainen.net/optimize.html. It is intended to be used only in demonstrating and testing of the optimization method, not in treating
patients.
64
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HEMO-equivalent and optimized prescriptions are
computed from V and G determined by double-pool
UKM from the actual data. Table 3 shows the actual and
simulated sessions.
In 80 (39%) of the simulated HEMO-equivalent sessions, the required blood flow is greater than the actual
maximum, which means that eKt/V 1.2 cannot be
achieved with the conventional schedule. The stdEKR
and stdK/V targets can still be computed despite this virtual Qb.
In 38 optimized sessions (19%), stdEKR or stdK/V is
over 10% higher than the HEMO-equivalent target due to
TAC and PAC limits. Average and minimum eKt/V are
in the optimized sessions lower than 1.2/session due to
RRF and/or higher frequency.
The simulated optimized treatments differ considerably from the conventionally prescribed actual ones. Actual average values of TAC and PAC are lower and average values of stdEKR and stdK/V are higher than the
optimized ones (table 3), but possible underdialysis is still
detected in six actual sessions (3%) by at least one clearance or concentration value differing more than 10%
from the optimized one. In 165 sessions (80%), both actual stdEKR and actual stdK/V are over 10% higher than
the optimized values. Low concentrations with normal
clearance are not interpreted as overdialysis. Overdialysis
means at least wasting of resources. In this material, optimization decreases the weekly treatment time and dialysate consumption (table 3).
Vartia
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Results
Simulations
The dialysis sessions were modified by computer simulations
with the double pool UKM, assuming that variations in dialysis do
not affect urea generation rate. Kd, td and fr were varied and concentrations, stdEKR and stdK/V, were calculated. By numeric solution of the UKM equations it was also possible to compute the
required Kd or td to achieve the desired concentrations or stdEKR
or stdK/V.
Dialyzer mass area coefficient (KoA) was calculated in each session from dialysate flow (Qd), blood flow (Qb) and online Kd [19].
This KoA was then used in simulations to compute the Qb and Qd
to achieve the required Kd.
Table 3. Actual and simulated sessions
Treatment frequency
Average, week
Minimum, week
Maximum, week
SD, week
Treatment time
Average, min
Minimum, min
Maximum, min
SD, min
eKt/V
Average
Minimum
Maximum
SD
stdEKR
Average, week
Minimum, week
Maximum, week
SD, week
stdK/V
Average, week
Minimum, week
Maximum, week
SD, week
TAC
Average, mmol/l
Minimum, mmol/l
Maximum, mmol/l
SD, mmol/l
PAC
Average, mmol/l
Minimum, mmol/l
Maximum, mmol/l
SD, mmol/l
Weekly treatment time
Average, h
SD, h
Weekly dialysate consumption
Average, l
SD, l
HEMO
Optimized
3.11
2.00
4.45
0.33
3.00
3.00
3.00
0.00
2.96
2.00
4.00
0.33
297
243
485
40
240
240
240
0
250
240
299
17
1.47
0.93
2.39
0.26
1.20
1.20
1.20
0.00
1.18
0.76
2.03
0.18
4.65
3.08
6.31
0.61
3.44
3.23
3.61
0.08
3.56
3.23
5.29
0.29
2.96
2.12
3.78
0.32
2.35
2.15
2.53
0.07
2.47
2.17
3.47
0.20
12.4
4.7
25.7
3.6
16.5
6.8
30.0
4.6
15.8
6.8
20.1
3.6
19.3
7.5
36.3
5.5
24.2
9.8
44.7
6.7
22.8
9.8
30.0
5.2
15.4
2.4
12.0
0.0
12.3
1.5
459
65
360
0
302
95
By optimization, 173 (84%) of the actual sessions fall
into the 3×/week schedule, 15 (7%) need more; in 17 (8%)
2×/week is sufficient (table 4). These proportions are of
course dependent on the targets (table 2).
Table 4 may be interpreted as follows: with normal
nPCR, two sessions per week is sufficient only if the patient has moderate RRF, but with high nPCR, a high frequency is required to achieve the TAC and PAC targets
despite RRF, and this is reflected in high clearances.
Adjusting Hemodialysis Dose
fr,
week
Sessions, Kr,
n
ml/min
nPCR,
g/kg/day
stdEKR,
week
stdK/V,
week
2
3
3.5
4
17
173
12
3
1.09±0.22
1.06±0.24
1.35±0.28
1.74±0.12
3.52±0.23
3.51±0.19
3.91±0.44
4.87±0.40
2.35±0.18
2.44±0.14
2.74±0.24
3.37±0.11
Sum
205
3.2±1.3
0.6±1.1
0.6±0.9
2.1±1.1
fr = treatment frequency; Sessions = number of sessions in each
frequency category; Kr = renal blood water urea clearance; nPCR =
normalized protein catabolic rate.
In 43 sessions (21%), the optimized dialysis dose is determined by the concentration limits. The HEMO-equivalent clearance is not enough to keep TAC and PAC below
the defined upper limits (20 and 30 mmol/l), if nPCR is
greater than 1.3 g/kg/day. Figure 1 summarizes the results.
Discussion
In this model, the hemodialysis dose is scaled not only
to body size but also to the protein catabolic rate by cutting high urea concentrations. The optimized prescription fulfills the conventional clearance-based adequacy
criteria (stdEKR and stdK/V), but if this is not enough to
guarantee moderate concentrations, the dose is increased.
This means more individualized dosing. The nPCR value
above which the clearance-based prescription is modified
by the protein catabolic rate (about 1.3 g/kg/day; fig. 1)
depends of course on the concentration limits.
The optimized prescription shows how the patient
should have been dialyzed according to this model. The patient-specific variables V and G are derived by UKM from
real dialysis sessions. Online clearance is used as Kd in the
UKM. The optimization procedure calculates a new Kd
and determines the required Qb and Qd from it and KoA,
which is calculated from the actual Qb, Qd and online Kd.
The new Qb and Qd can be applied to next treatments, if
the patient-specific parameters and other circumstances remain constant. Kd from the OCM device can be compared
to the prescribed one. The measured and prescribed Kd, Qb
and Qd are commensurable and have same error sources.
Creating an accurate prescription is possible by kinetic
modeling, but the patient’s G, V and Kr can vary between
sessions and there are significant error sources in measurBlood Purif 2014;38:62–67
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65
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Actual
Table 4. Optimized sessions: frequency distribution and values by
frequency (average ± SD)
6
30
25
5
25
5
20
4
20
4
15
3
15
3
10
2
10
2
5
1
5
1
0
0
TAC (mmol/l)
0
stdEKR
0
0.4
0.8
1.2
nPCR (g/kg/day)
1.6
2.0
7
PAC
6
stdK/V
0
0.4
0.8
1.2
nPCR (g/kg/day)
1.6
2.0
stdK/V (week)
TAC
30
PAC (mmol/l)
35
stdEKR (week)
7
35
0
Fig. 1. TAC, PAC, stdEKR and stdK/V plotted against nPCR in the optimized sessions.
66
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Urea concentrations can be efficiently decreased by increasing treatment frequency. Increasing dialyzer clearance (KoA, Qb, Qd, Kt/V) is an inefficient way to decrease
PAC and increase stdK/V. In this material with simulated
3 × 4 h/week schedule without RRF, increasing Kd by 34%
from the average 191 ml/min to 256 ml/min (eKt/V from
1.2 to 1.6) resulted in 12% fall of average PAC from 24.2 to
21.4 mmol/l and 13% rise of stdK/V from 2.35 to 2.66/week.
Increasing frequency in a whole dialysis population
had some favorable effects on outcome in the FHN trials,
but ‘the net effects of frequent hemodialysis will need to
be balanced against the added burden for the patient and
societal cost’ [21]. Concentration limits may help in selecting patients who might benefit from high frequency.
We don’t know the optimal or critical upper limits of
TAC and PAC or whether they exist. A computer is needed in creating a multi-target prescription, but after seeing
a high predialysis urea concentration it is usually rather
simple to intensify the treatment, if we accept that it is justified. High concentration is either due to a low clearance
or due to a high generation rate. In both cases, the dialysis
dose needs to be increased – if the hypothesis that patients
with a high nPCR value benefit from higher dose is true.
Is it reasonable to be satisfied with an adequate Kt/V if
concentrations are high? This study does not answer this
question, but presents a solution, if the answer is ‘no’.
Support and Disclosure Statement
No support, no funding, no conflicts of interest.
Vartia
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ing them. In this study, the session-specific KoA values,
based on online clearance, Qb and Qd, had considerable
variation within each dialyzer model (not shown), which
refers to some uncontrolled factors. Using a symmetric
schedule in demonstrating the optimization principle is a
shortcut, which simplifies the procedure and shortens the
computer time, but it is an extra source of inaccuracy.
In a recent study, women had higher urea concentrations than men when simulating dialysis with equal
eKt/V, stdEKR or stdK/V [5]. Dialyzing to an equal concentration would deliver more Kt/V to women. In the
HEMO study, women but not men benefitted from the
higher eKt/V. This is at least partially associated to scaling
by V. Adjusting dialysis dose for protein catabolic rate by
concentration limits modifies the scaling.
There are no investigations confirming the hypothesis
that patients having high urea concentrations with conventional clearance would benefit from more intensive
dialysis. The optimization procedure described here is
based on 205 hemodialysis sessions of 33 individual patients. It is absolutely impossible to confirm the hypothesis in this scale. Perhaps it could be confirmed or discarded by reanalyzing the HEMO material. Kt/V and
nPCR were monitored monthly and there was considerable variation in nPCR at baseline [20]. Did patients with
high nPCR benefit from the higher dose? The role of
nPCR is more difficult to assess than that of gender because it may change during the study, the dialysis dose
may have an effect on it and there may be a mathematical
coupling between Kt/V and nPCR. However, the HEMO
investigators could probably overcome these difficulties.
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