Original Article
Association of Body Mass Index and Long-Term Outcomes
in Older Patients With Non–ST-Segment–Elevation
Myocardial Infarction
Results From the CRUSADE Registry
Emily C. O’Brien, PhD; Emil L. Fosbol, MD, PhD; S. Andrew Peng, MS;
Karen P. Alexander, MD; Matthew T. Roe, MD, MHS; Eric D. Peterson, MD, MPH
Background—Prior studies have found that obese patients have paradoxically lower in-hospital mortality after non–STsegment–elevation myocardial infarction than their normal-weight counterparts, yet whether these associations persist
long term is unknown.
Methods and Results—We linked detailed clinical data for patients with non–ST-segment–elevation myocardial infarction
aged ≥65 years in the Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early
Implementation of the American College of Cardiology/American Heart Association Guidelines (CRUSADE) Registry
to Medicare claims data to obtain longitudinal outcomes. Using height and weight measured on admission, patients were
categorized into 6 body mass index (BMI [kilograms per meter squared]) groups. Multivariable Cox proportional hazards
models were used to estimate the association between BMI and (1) all-cause mortality, (2) all-cause readmission, (3)
cardiovascular readmission, and (4) noncardiovascular readmission for 3 years after hospital discharge. Among older
patients with non–ST-segment–elevation myocardial infarction (n=34 465), 36.3% were overweight and 27.7% were
obese. Obese patients were younger and more likely to have hypertension, diabetes mellitus, and dyslipidemia than
normal or underweight patients. Relative to normal-weight patients, long-term mortality was lower for patients classified
as overweight (BMI, 25.0–29.9), obese class I (BMI, 30.0–34.9), and obese class II (BMI, 35.0–39.9), but not obese
class III (BMI ≥40.0). In contrast, 3-year all-cause and cardiovascular readmission were similar across BMI categories.
Relative to normal-weight patients, noncardiovascular readmissions were similar for obese class I but higher for obese
class II and obese class III.
Conclusions—All-cause long-term mortality was generally lower for overweight and obese older patients after non–STsegment–elevation myocardial infarction relative to those with normal weight. Longitudinal readmissions were similar or
higher with increasing BMI. (Circ Cardiovasc Qual Outcomes. 2014;7:102-109.)
Key Words: acute coronary syndrome ◼ obesity
A
lthough it is well established that obesity increases the risk
for incident cardiovascular (CV) disease,1 prior work has
reported that obese patients experience paradoxically better inhospital outcomes than their normal body mass index (BMI)
counterparts after heart failure,2,3 chronic kidney disease,4 coronary artery disease,5 and diabetes mellitus.6 This obesity paradox
has been well documented for short-term mortality and may be at
least partially explained by more aggressive in-hospital management of overweight and obese patients.7,8 Nevertheless, whether
or not this effect persists long term is unclear. Furthermore,
much of the published data represent younger acute coronary
syndrome populations, and less information exists on the impact
of BMI on outcomes after non–ST-segment–elevation myocardial infarction (NSTEMI) in older adults.9
We examined the association between BMI and all-cause
mortality, CV rehospitalization, and non-CV rehospitalization
during 3 years of follow-up in a population of older patients
with NSTEMI.
Methods
Study Population
We used data from the Can Rapid Risk Stratification of Unstable Angina
Patients Suppress Adverse Outcomes With Early Implementation of
the American College of Cardiology/American Heart Association
Guidelines (CRUSADE) NSTEMI Registry linked to Medicare claims
to obtain longitudinal outcomes. Details of the CRUSADE study design have been previously published.10 Briefly, CRUSADE was a national hospital-based initiative designed to track adherence to treatment
guidelines and improve the quality of care for patients with NSTEMI.
Received June 17, 2013; accepted October 28, 2013.
From the Departments of Clinical Pharmacology (E.C.O., K.P.A., M.T.R., E.D.P.) and Outcomes Research (S.A.P.) Duke Clinical Research Institute,
Durham, NC; and Department of Cardiology, Gentofte University Hospital, Hellerup, Denmark (E.L.F.).
This article was handled independently by Karol Watson, MD, as a Guest Editor. The Editors had no role in the evaluation of the manuscript or the
decision about its acceptance.
Correspondence to Emily O’Brien, PhD, Duke Clinical Research Institute, 2400 Pratt St, Durham, NC 27705. E-mail [email protected]
© 2013 American Heart Association, Inc.
Circ Cardiovasc Qual Outcomes is available at http://circoutcomes.ahajournals.org
DOI: 10.1161/CIRCOUTCOMES.113.000421
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by guest on March 5, 2016
102
O’Brien et al BMI and Long-Term Outcomes 103
WHAT IS KNOWN
• Although obesity increases the risk of cardiovascular
disease, prior studies have reported lower in-hospital
mortality in obese patients with non–ST-segment–
elevation myocardial infarction relative to those with
normal body mass index.
• This association may be at least partially explained
by more aggressive in-hospital management of overweight and obese patients.
WHAT THE STUDY ADDS
• In this large cohort of elderly patients with non–STsegment–elevation myocardial infarction , we found
a U-shaped association between weight and all-cause
mortality after non–ST-segment–elevation myocardial infarction, with lower mortality among overweight or obese patients.
• Adjusting for in-hospital treatment did not substantially alter observed associations between body mass
index and adverse outcomes, suggesting that the protective effects of increasing body mass index persist
despite accounting for more aggressive management.
• Rates of hospital readmissions over 3 years among
obese and overweight patients were similar or higher
than their normal-weight counterparts.
Trained abstractors collected data on demographics, medical history,
signs and symptoms on presentation, laboratory values (including cardiac biomarkers), in-hospital treatments and interventions, discharge
therapies, and clinical outcomes for eligible patients. Participating
sites were required to obtain approval from local institutional review
boards (or equivalent) before data entry.
To capture postdischarge outcomes, we used a previously validated
methodology to link clinical data from 442 CRUSADE hospitals to
Medicare claims data.9 Specifically, data from 2003 to 2006 on 42 568
patients with NSTEMI aged ≥65 years who were alive and enrolled
in Medicare at the time of discharge were linked to Medicare Part
A claims (hospitalizations) using a set of indirect patient identifiers.
The Duke University Medical Center Institutional Review Board reviewed this study and granted a waiver of the requirement for informed consent and authorization. We excluded patients who were
transferred to other facilities (n=4474), patients who had missing information on height and weight (n=2300), and nonindex admissions
for patients with multiple records (n=1329) for a final study population of 34 465 patients.
Body Mass Index
BMI was calculated using weight and height values recorded on hospital admission. Patients were categorized into the following 6 BMI
classes according to World Health Organization standards11: (1) underweight (BMI <18.5 kg/m2); (2) normal weight (BMI, 18.5–24.9
kg/m2); (3) overweight (BMI, 25.0–29.9 kg/m2); (4) obese I (BMI,
30.0–34.9 kg/m2); (5) obese II (BMI, 35.0–39.9 kg/m2); and (6) obese
III (BMI ≥40.0 kg/m2). BMI was treated as a categorical variable for
all analyses.
Outcomes
We searched Medicare claims records for information on vital status
and rehospitalization for 3 years after hospital discharge. All-cause
mortality was ascertained from Medicare denominator files. We used
Medicare Part A inpatient claims to identify subsequent all-cause hospitalizations occurring during the 3-year period after discharge. In addition, hospitalizations were classified as either CV related or non-CV
related based on a prespecified set of International Classification of
Diseases, Ninth Revision discharge codes.12 Because of the possibility
of planned readmission for revascularization procedures after NSTEMI
hospitalization, we excluded readmissions for percutaneous coronary
intervention (PCI) or coronary artery bypass graft surgery within 60
days of hospital discharge, unless these readmissions were accompanied by a discharge diagnosis that was clearly inconsistent with an
elective readmission (ie, heart failure, acute myocardial infarction,
unstable angina, arrhythmia, and cardiac arrest). Finally, we created
a composite end point of all-cause mortality and CV rehospitalization.
Statistical Analysis
We compared distributions of baseline patient and event characteristics among BMI categories. Differences between BMI groups were assessed using χ2 tests for categorical variables and Kruskal–Wallis tests
for continuous variables. We used univariable and multivariable Cox
proportional hazard models to estimate unadjusted and adjusted associations separately for each end point of all-cause mortality, CV rehospitalization, non-CV rehospitalization, and the composite end point of
CV rehospitalization and all-cause mortality. The normal-weight BMI
category (BMI, 18.5–24.9 kg/m2) was used as the referent group for all
models. All multivariable models were adjusted using a modified set
of variables from the CRUSADE long-term mortality model, controlling for age, sex, race, family history of coronary artery disease, current or recent smoking status, prior myocardial infarction, prior PCI,
prior coronary artery bypass graft, prior congestive heart failure, prior
stroke, heart failure at presentation, heart rate, electrocardiographic
findings, initial hematocrit, and initial troponin ratio.13 Patients were
censored at 3 years after hospital discharge in mortality models and
on the date of death, on losing fee-for-service eligibility, or at 3 years
postdischarge in rehospitalization models. By censoring at the time of
mortality, we evaluate associations with the cause-specific hazard for
nonfatal end points. This can be interpreted as the hazard ratio among
patients who remain at risk (alive and under follow-up). Follow-up
information for all-cause mortality at 3 years was complete for all
patients. Approximately 5% of patients in the readmission analysis
were lost to follow-up because of loss of Medicare Part A eligibility.
The percentage of missing values for all variables used in regression analyses ranged from 0% to 3%. In adjusted models, missing
values were imputed to the median of nonmissing values for continuous covariates and the most frequent category for categorical variables. All statistical analyses were performed using SAS software
version 9.2 (SAS Institute, Cary, NC).
Results
Characteristics of the patient population at hospital admission
are shown in Table 1. The majority of patients in CRUSADECMS (Centers for Medicare and Medicaid Services)were overweight or obese (64.0%). The largest proportion of patients
were classified as overweight (36.3%), followed by normal
weight (32.5%), obese class I (17.7%), obese class II (6.5%),
underweight (3.6%), and obese class III (3.6%). We observed
an inverse association between BMI and age, with a median
age of 72 years (interquartile range, 68–77) for obese class III,
compared with a median age of 80 years (interquartile range,
74–86) in the normal-weight group. Obese patients had higher
rates of comorbidities, including hypertension, diabetes mellitus, and dyslipidemia than n­ ormal-weight patients. Normalweight and underweight patients were significantly more likely
to be smokers than overweight and obese patients. Signs and
symptoms at presentation were similar across categories, with
the exception of heart rate, which was highest in underweight
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104 Circ Cardiovasc Qual Outcomes January 2014
Table 1. Baseline Patient and Event Characteristics by Body Mass Index Category
Variable
Underweight*
(n=1236)
Normal Weight
(n=11 186)
Overweight
(n=12 506)
Obese I (n=6089)
Obese II (n=2226)
Obese III (n=1222)
P Value†
Demographics
Age, y
Male sex
Weight, kg
White race
82 (75–88)
30.7
80 (74–86)
77 (71–82)
49.3
75 (69–80)
59.4
45.4 (41.3–50.1) 63.0 (56.2–70.3) 78.1 (70.8–85.7)
73 (69–79)
54.7
46.1
90.5 (81.6–99.8)
101.2 (90.9–111.9)
72 (68–77)
35.5
<0.0001
<0.0001
117 (104.6–132.0) <0.0001
83.8
86.7
86.7
86.5
86.3
84.4
<0.0001
Hypertension
71.1
73.5
76.2
81.2
84.6
86.2
<0.0001
Diabetes mellitus
16.9
25.4
34.3
44.8
55.7
61.1
<0.0001
Dyslipidemia
33.9
46.5
54.6
59.3
60.7
58.9
<0.0001
Current/recent smoker
19.7
14.3
12.5
10.6
10.1
9.9
<0.0001
Family history of CAD
21.0
24.4
28.0
29.6
31.4
30.4
<0.0001
Prior PAD
13.8
15.2
14.6
14.3
13.3
14.2
0.1880
Prior CHF
29.0
23.6
19.9
20.6
24.1
32.1
<0.0001
Prior MI
26.9
30.6
30.3
31.3
30.9
29.5
0.0815
Prior stroke
15.3
14.8
12.6
12.5
12.5
12.4
<0.0001
Prior CABG
15.2
22.6
25.2
25.0
24.8
21.2
<0.0001
Prior PCI
13.0
18.7
22.1
24.3
24.8
25.2
<0.0001
Medical history
Signs/symptoms at presentation
Signs of HF
SBP
Heart rate, bpm
Hematocrit, %
35.4
31.4
27.5
27.6
30.2
137 (116–159)
142 (121–163)
145 (125–166)
147 (127–168)
147 (126–170)
90 (76–107)
85 (71–102)
82 (70–99)
37.6 (33.7–41.2) 38.3 (34.4–42.0) 39.5 (35.6–43.0)
36.3
147 (128–170)
<0.0001
<0.0001
83 (70–100)
84 (70–100)
87 (74–103)
<0.0001
39.8 (35.9–43.4)
39.8 (35.7–43.1)
38.8 (35.1–42.4)
<0.0001
<0.0001
Creatinine, mg/dL
1.1 (0.9–1.4)
1.2 (0.9–1.5)
1.2 (1.0–1.5)
1.2 (1.0–1.5)
1.2 (0.9–1.5)
1.2 (1.0–1.6)
Troponin ratio, ×ULN
3.2 (1.0–12.0)
2.4 (0.7–10.3)
2.0 (0.6–9.3)
2.0 (0.5–8.7)
1.8 (0.4–7.8)
1.9 (0.4–7.2)
24.2
28.5
27.3
26.6
26.2
25.7
Transient ST elevation
3.6
3.6
3.2
3.2
3.4
2.5
Both
0.7
0.8
1.1
0.5
0.4
0.6
ECG findings
ST depression
<0.0001
All data are presented as percentages except age, weight, SBP, heart rate, hematocrit, and creatinine which are presented as median (interquartile range). CABG
indicates coronary artery bypass grafting; CAD, coronary artery disease; CHF, congestive heart failure; HF, heart failure; MI, myocardial infarction; PAD, peripheral artery
disease; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; and ×ULN, times upper limit of normal.
*World Health Organization body mass index categories (kilograms per meter squared): underweight <18.5; normal weight, 18.5–24.9; overweight, 25.0–29.9; obese
class I, 30.0–34.9; obese class II, 35.0–39.9; obese class III ≥40.0.
†P values from χ2 tests for categorical variables and Kruskal–Wallis tests for continuous variables.
and obese class III patients. Signs of heart failure were least
common among overweight and obese class I patients.
Table 2 shows the use of in-hospital medications, invasive
procedures, discharge medications, and in-hospital events by
BMI category. In the first 24 hours of hospitalization, overweight and obese patients were more likely to receive aspirin, glycoprotein IIa/IIIb inhibitors, and clopidogrel than
normal-weight patients. Rates of invasive procedures, including cardiac catheterization, PCI, and coronary artery bypass
graft, were also higher among overweight and obese patients
than among normal-weight patients. At hospital discharge,
angiotensin-converting enzyme inhibitors/angiotensin receptor blockers and lipid-lowering medications were more commonly prescribed to overweight and obese patients than to
normal-weight patients. The lowest rates of both CRUSADE
major bleeding events and in-hospital congestive heart failure
were observed among overweight, obese class I, and obese
class II patients. No significant differences in rates of cardiogenic shock were found between BMI groups.
Conditional on surviving to hospital discharge, all-cause
mortality at 3 years in the total study population was 36.6%.
Unadjusted 3-year mortality was highest among underweight patients (62.4%), followed by normal-weight patients
(45.6%). Obese class I patients had the lowest 3-year rates of
unadjusted mortality of the 6 BMI groups (28.0%; Figure 1).
Unadjusted and adjusted hazard ratios for all-cause mortality, rehospitalization (CV and non-CV), and the composite end point of death and CV rehospitalization are shown
for the 6 BMI classes in Figure 2 (unadjusted) and Figure 3
(adjusted). After adjustment, when compared with normalweight patients, overweight and obese patients class I and
II had lower all-cause mortality, obese class III patients had
similar outcomes, and underweight patients had significantly
higher mortality.
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O’Brien et al BMI and Long-Term Outcomes 105
Table 2. In-Hospital and Discharge Medications, Procedures, and Clinical Events BMI Category
Underweight*
(n=1236)
Normal Weight
(n=11 186)
Overweight
(n=12 506)
Obese I (n=6089)
Obese II (n=2226)
Obese III (n=1222)
P Value†
Aspirin
93.2
95.3
96.0
95.7
94.8
93.4
<0.0001
Clopidogrel
45.8
52.6
56.0
55.2
54.8
51.2
<0.0001
GP IIb/IIIa inhibitor
26.6
36.8
44.5
44.8
42.3
36.9
<0.0001
Heparin (LMWH or UFH)
85.1
85.9
89.1
88.9
88.3
87.6
<0.0001
β-Blocker
88.2
89.3
90.7
90.1
90.0
90.0
0.0149
Cardiac catheterization
41.6
58.2
72.8
76.2
76.2
71.8
<0.0001
PCI
20.3
31.3
41.7
43.2
42.5
40.3
<0.0001
3.9
7.9
11.7
12.4
11.8
7.9
<0.0001
Aspirin
91.8
93.3
94.7
95.1
94.7
94.1
<0.0001
Clopidogrel
60.1
67.3
71.6
71.6
73.0
70.0
<0.0001
β-Blocker
89.8
91.7
92.5
92.0
93.2
90.8
<0.0001
ACE inhibitor or ARB
60.4
63.8
65.7
68.9
69.2
68.1
<0.0001
Lipid-lowering agent
60.3
72.5
80.1
81.6
82.6
79.9
<0.0001
1.7
1.7
1.6
1.5
1.6
1.2
0.7051
CHF
10.6
10.3
8.4
8.5
9.5
10.6
<0.0001
CRUSADE major bleeding
13.4
12.3
11.0
10.6
11.5
14.7
<0.0001
Variable
Acute medications
In-hospital procedures
CABG
Discharge medications
In-hospital clinical events
Cardiogenic shock
All data are presented as percentages. ACE indicates angiotensin-converting enzyme; ARB, angiotensin receptor blocker; BMI, body mass index; CABG, coronary
artery bypass grafting; CHF, congestive heart failure; CRUSADE, Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early
Implementation of the American College of Cardiology/American Heart Association Guidelines; GP IIb/IIIa, glycoprotein IIb/IIIa; LMWH, low-molecular-weight heparin;
PCI, percutaneous coronary intervention; and UFH, unfractionated heparin.
*World Health Organization BMI categories (kilograms per meter squared): underweight <18.5; normal weight, 18.5–24.9; overweight, 25.0–29.9; obese class I,
30.0–34.9; obese class II, 35.0–39.9; obese class III ≥40.0.
†Based on Pearson χ² tests for categorical variables and Kruskal-Wallis tests for continuous variables
Being overweight was associated with a modest reduction
in all-cause readmission, but this effect was attenuated for
obese class I patients and reversed for obese class II and III
patients (Figure 3). Adjusted risk of CV readmission was similar across BMI categories. We observed a lower unadjusted
risk of non-CV rehospitalization among overweight and obese
class I patients, but this effect was attenuated after adjustment.
Underweight patients had a slightly higher adjusted risk of nonCV readmission compared with normal-weight patients. For
the composite end point of all-cause mortality and CV readmission, overweight and obese patients had lower unadjusted
rates than normal-weight patients; however, absolute differences in rates of the composite end point were minimal after
adjustment. Being underweight was associated with a slightly
higher risk of the composite end point after adjustment.
Discussion
To our knowledge, this is the first study of long-term outcomes
and BMI in an older NSTEMI population. We had several major
findings. First, the majority of older patients with NSTEMI
were overweight or obese (64.0%). Second, age at time of
myocardial infarction varied inversely with BMI; the oldest
patients were in the underweight and normal-weight categories,
whereas the youngest patients were in the obese class II and III
categories. Third, overweight and obese patients generally have
similar or lower all-cause mortality for 3 years after NSTEMI.
Finally, although adjusted rates of CV rehospitalization were
comparable across BMI categories, non-CV–related rehospitalization was similar or higher with increasing BMI.
The findings from our study are largely consistent with those
who have previously reported short-term survival benefits associated with obesity during and directly after acute coronary syndrome hospitalization. In 1 study of BMI and CV outcomes
among 4762 patients undergoing PCI in Australia, increasing
BMI was associated with linear reductions in major adverse
CV events both in hospital and at 12 months postdischarge.14
Results from the long-term follow-up of 6560 non–ST-segment acute coronary syndrome participants in the Metabolic
Efficiency With Ranolazine for Less Ischemia in Non–STElevation Acute Coronary Syndromes-Thrombolysis in
Myocardial Infarction (MERLIN-TIMI) 36 trial suggest the
short-term protective effect of obesity.15 Finally, in a follow-up
study of 7427 patients undergoing PCI with drug-eluting stents,
lower rates of mortality at 5 years were reported for overweight
and obese patients compared with normal-weight patients.16
Several physiological and methodological explanations for
the obesity paradox have been presented, with varying levels
of empirical support. First, we examined long-term outcomes
by BMI in an older population (aged ≥65 years) of patients
with NSTEMI. Although excess body weight seems to be
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106 Circ Cardiovasc Qual Outcomes January 2014
Figure 1. Mortality incidence by body mass index (BMI) category. Unadjusted cumulative incidence of mortality (%) by BMI category*
during 3 years of follow-up is displayed. *World Health Organization BMI categories (kilograms per meter squared): underweight <18.5;
normal weight, 18.5 to 24.9; overweight, 25.0 to 29.9; obese class I, 30.0 to 34.9; obese class II, 35.0 to 39.9; obese class III ≥40.0.
protective in older populations, the observed direction of this
effect is often reversed in younger cohorts, suggesting that
these associations are likely age dependent.17,18 In addition, it
has been hypothesized that unexpected BMI mortality associations may be the result of study design.19 The obesity paradox
has been documented largely in observational, disease-based
registries, which are vulnerable to issues of selection bias.
Because obese patients experience acute coronary events at
younger ages20 and have shorter life expectancy than normalweight patients,20 it is possible that only the healthiest obese
patients survive long enough to be hospitalized and captured in
these study populations. If unmeasured extraneous factors are
present among the older obese patients that both confer a survival advantage and are not present in normal-weight participants, bias may be introduced to mortality estimates. This type
of survival bias is more evident in associations with short-term
outcomes and theoretically diminishes with increasing followup time.21 Nonetheless, we observed lower mortality among
overweight and obese patients for 3 years after discharge, suggesting a protective effect that persists beyond the short term.
In addition to population-level hypotheses, some evidence
suggests that obesity’s protective effect operates through biological mechanisms that differ by BMI subclass. Compared
with patients in normal and low BMI categories, patients
with high BMI are likely to have increased total lean mass
in addition to increased adiposity—both of which may offer
advantages in the context of acute CV disease. Lean mass
has important homeostatic benefits, including better glucose
and oxygen metabolism, which may positively influence survival.21 Patients in normal and low BMI categories are more
likely to have low levels of lean mass, a condition associated
with metabolic dysregulation and increased mortality.22
Furthermore, because low BMI is associated with lower adiposity, patients in underweight and normal-weight categories
may be more vulnerable to adverse cardiometabolic effects of
chronic disease.23 Patients experiencing acute events undergo
catabolic changes, including inflammation and activation of
neurohormonal systems, which require additional energy
reserves.22 Increased subcutaneous fat may provide resistance
to the catabolic burden associated with acute cardiac events.
Finally, a developing explanation for the obesity paradox
suggests that more aggressive treatment is received by overweight and obese patients during the index hospitalization.
Physicians may perceive overweight and obese patients to be
at higher risk for adverse outcomes or be more likely to recognize comorbidities and thus may be more likely to prescribe
evidence-based therapies and interventions to patients with
higher BMI. In a 2006 analysis of BMI and in-hospital mortality in CRUSADE, Diercks et al8 reported increased use of diagnostic catheterization, PCI, and coronary artery bypass graft
among overweight and obese patients compared with those
of a normal weight. Nevertheless, adding treatment received
to models of in-hospital mortality did not substantially alter
observed associations between BMI and adverse outcomes,
suggesting that the protective effects of increasing BMI persist despite accounting for more aggressive management.
Our study has several limitations. First, although we were able
to examine mortality and rehospitalization outcomes up to 3 years
postdischarge, it is possible that obesity is not protective beyond
this time period. Because we were limited to a single measurement of BMI on hospital admission, we were unable to assess
the impact of changes in weight status over time. Second, prior
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O’Brien et al BMI and Long-Term Outcomes 107
Figure 2. Body mass index (BMI) and unadjusted postdischarge outcomes. Adjusted hazard ratios (HRs) and 95% confidence intervals
(CIs) for BMI* and postdischarge outcomes are displayed. CV indicates cardiovascular. *World Health Organization BMI categories
(kilograms per meter squared): underweight <18.5; normal weight, 18.5 to 24.9; overweight, 25.0 to 29.9; obese class I, 30.0 to 34.9;
obese class II, 35.0 to 39.9; obese class III ≥40.0.
studies have reported positive mortality associations for other
measures of adiposity, such as waist-to-hip ratio or waist circumference.15,23 Because these were not captured in CRUSADE, we
were unable to examine whether these associations persisted in
our study population. Third, because cause-of-death information
was not available in our study, we were unable to assess whether
BMI associations persisted by death classification. Fourth, our
population experienced a high rate of mortality, which represents a competing risk for nonfatal end points. We handled this
by studying associations with the cause-specific hazard, which is
estimable from the observed data, but does not provide an indication of what could have happened if death did not occur. Finally,
because we evaluated the association between obesity and longterm mortality after NSTEMI in an older, mostly white population, our results may not be generalizable to younger populations
or those with different racial or ethnic distributions.
In summary, we found that overweight and obese patients
with NSTEMI experience lower all-cause mortality than their
normal-weight counterparts for 3 years after hospital discharge. Further examination is needed regarding the possible
mechanisms for obesity’s protective effect in older acute coronary syndrome populations.
Acknowledgments
We thank the staff and participants of the CRUSADE Registry for
their important contributions to this work. We also thank Erin LoFrese
for her editorial contributions to this manuscript.
Sources of Funding
CRUSADE was funded by Millennium Pharmaceuticals, Schering-Plough
Corporation, and the Bristol-Myers Squibb/Sanofi Pharmaceuticals
Partnership. This work was supported internally by the Duke Clinical
Research Institute, which donated support for these analyses.
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108 Circ Cardiovasc Qual Outcomes January 2014
Figure 3. Body mass index (BMI) and adjusted postdischarge outcomes. Adjusted hazard ratios (HRs)* and 95% confidence intervals
(CIs) for BMI† and postdischarge outcomes are displayed. CV indicates cardiovascular. *Models adjusted for age, sex, race, family history
of coronary artery disease, current or recent smoking status, prior myocardial infarction, percutaneous coronary intervention, coronary
artery bypass graft, congestive heart failure, prior stroke, heart failure at presentation, heart rate, ECG findings, initial hematocrit, and
initial troponin ratio. †World Health Organization BMI categories (kilograms per meter squared): underweight <18.5; normal weight, 18.5
to 24.9; overweight, 25.0 to 29.9; obese class I, 30.0 to 34.9; obese class II, 35.0 to 39.9; obese class III ≥40.0.
Disclosures
References
Dr Alexander reports consultant fees/honoraria from Gilead and
Pozen; other relationships (Safety Monitoring and Sub Investigator)
from Sanofi-aventis; and research/research grants from Gilead and
Sanofi-aventis. Dr Roe reports research funding from Eli Lilly and
Company, KAI Pharmaceuticals, and Sanofi-Aventis (all significant); educational activities or lectures for AstraZeneca and Janssen
Pharmaceuticals (both modest); consulting for Bristol Myers Squibb,
Eli Lilly and Company, GlaxoSmithKline, and Regeneron (all modest), Merck & Co., Janssen Pharmaceuticals, and Daiichi-Sankyo (all
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Company, Ortho-McNeil-Janssen Pharmaceuticals, Inc., Society of
Thoracic Surgeons, American Heart Association, American College of
Cardiology (all significant); consulting for AstraZeneca, Boehringer
Ingelheim, Genentech, Johnson & Johnson, Ortho-McNeil-Janssen
Pharmaceuticals, Inc., Pfizer, Sanofi-Aventis, and WebMD (all modest). The other authors report no conflicts.
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Association of Body Mass Index and Long-Term Outcomes in Older Patients With Non−
ST-Segment−Elevation Myocardial Infarction: Results From the CRUSADE Registry
Emily C. O'Brien, Emil L. Fosbol, S. Andrew Peng, Karen P. Alexander, Matthew T. Roe and
Eric D. Peterson
Circ Cardiovasc Qual Outcomes. 2014;7:102-109; originally published online December 10,
2013;
doi: 10.1161/CIRCOUTCOMES.113.000421
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