Neuropsychiatric Sequelae and Life Events: Analysis and Management with e-Diaries
1 Department
Ronald Calvanio, PhD1, Ferdinando S. Buonanno, MD1 , David N. Levine, MD2 , Minna Levine, PhD3
of Neurology, Massachusetts General Hospital, 2Department of Neurology, NYU Medical Center, 3 SymTrend, Inc.
Background
Results
Life events influence the expression of neuropsychiatric sequelae of stroke,
traumatic brain injury and CNS infection complicating symptom management.
Objectives
To characterize this influence in terms of trigger patterns identified through ediary data collection with the goal of improving symptom management.
Three hypotheses were tested and supported.
Hypothesis 1:
Symptom-event associations (SEAS) are common and identifiable.
Hypothesis 2:
SEAs are mediated by three types of event triggers.
Hypothesis 3:
Trigger specifics are clues to intervention that improve outcomes.
Findings: SEAs were common; they were identified in 13 of 15 cases and
occurred in 21 of 23 symptoms: cognitive failure (7), pain (4), fatigue (3),
sensorimotor including balance problems (3), emotional outbursts (2),
hypersomnia (1), dizziness (1), but not seizures (1) or minimization of illness
(1).
Findings: An episode trigger is an event occurrence followed by a symptom
occurrence-4/12 cases; see examples 1, 2, and 3 below. A gradient trigger is an
episode trigger whose magnitude is correlated with symptom magnitude -- i.e.,
symptom intensity, frequency or duration-4/12 instances; see examples 4 and 5
below. A modulatory trigger is an event that accentuates the impact of an episode
trigger or gradient trigger-4/12 instances; see example 6 below.
Findings: Trigger-based intervention's led to improvements in symptom
relief, 10/15 patients; coping, 11/15; daily functioning, 11/15; and all three,
7/15.
Patients
13 outpatients and 2 inpatients --with cerebrovascular disease, brain injury, or CNS
infection -- were studied after conventional investigation had not led to satisfactory
management of cognitive failure (7), pain (4), fatigue (3), sensorimotor abnormality (3),
emotional dysfunction (3), hypersomnia (1), dizziness (1) and seizures (1).
Conclusions
Our findings elaborate the nature of symptom-event association in a way that can improve patient care in cases where conventional investigation has not proved satisfactory. They also document the utility of e-diary data collection in the
management of neuropsychiatric conditions.
Method
An electronic diary system with individualized protocols enabled patients to record
symptom and event occurrence daily for 2 to 55 weeks and enabled clinicians to
analyze -- graphically and statistically – symptom-event associations.
Multi-Symptom Clusters
Emotional Outbursts
Spells
Case 1. A single event episode triggers symptom
occurrences.
The figure shows daily spell occurrence over twelve
weeks. The  in each week indicates the onset of a
spell. Subsequent ’s indicate successive days with
spells. When a spell series continued into the next
week -- i.e., Weeks 4 and 11 -- they are listed as  in
the next week -- i.e., Weeks 5 and 12. The number of
onset () days and the number of successive days (
) for each day of the week are tallied at the bottom of
the figure. The tally shows that spells typically
started on Mondays, suggesting that spells were
related to the transition from weekend relaxation to
work week intensity -- later confirmed by transitions
from vacations to work (not shown).
Headache
Case 4. A gradient trigger intensifies
symptoms.
The major symptom complaint was headache
intensity over the course of the day. Additional
complaints included episodes of aphasia or
sensory–motor abnormality. The gradient
event was a pace of the work day: number of
customer orders. The figure illustrates the
mean daily rating of pain intensity (A) and
total daily symptom incident counts (B) for
week 1 (dark column) and 2 (white column).
The fast-pace order was Monday, then
Tuesday, then Thursday. Symptom intensity
and frequency correspond.
Cross Tabulation of Days with TBI Failures vs. Days with Emotional Outburst
Incidents
Failures
TBI Cognitive Failure
Cognitive Failure
Outbursts
15
2
No Outbursts
5
16
Case 2. Two sequential events trigger the occurrence of symptom outbursts.
The symptom is an outburst of intense anger during a family disagreement. The outbursts were not
triggered by disagreements alone; the occurrence of a prior distressing cognitive failure also played
a role. The table documents their combined impact. The columns indicate days with a brain-injury
(BI) related cognitive failure and days with none. The rows indicate days with an outburst and days
with none. There is a tight correlation between BI-related cognitive failures and outbursts (χ2 =
53.61, p<0.001). Thus, disagreements alone were not sufficient to produce outbursts.
Attention Lapses
Case 5. A gradient trigger precipitates multiple symptoms.
The gradient trigger is hours of intense activity including study, classes, and sports. The
symptoms are attention lapses. The scatter plot shows the relationship between hours of
intense activity (x axis), and number of attention lapses (y axis). The color coding of data
points highlight a step function relationship: At seven hours there is a step transition from at
most 2 lapses (22%) to 2 or more lapses (44%) per day.
Case 3. A dual event triggers the occurrence of symptom clusters.
The dual event –menses plus night sweats- is indicated lines 1 and 2. On line 1,
menses occurrence is indicated by hash marks. On line 2, night sweats occurrence is
indicated by hash marks. Line 3 shows the number of neurologic incidents per day
(scale at right). The incidents were dropping something, unsteadiness, falling,
numbness/tingling, forgetfulness, getting lost driving, and urinary incontinence. The
symptom clusters occur almost exclusively after dual incident occurrences.
Chronic Fatigue
Case 6. One event is modulated by a second
event.
The first event is energy level and the second is
level of feeling in control. The figure shows
their impact on effortful activity. In Panel A,
effortful activity per week, - - -, is plotted
relative to weekly levels of Feelings of Control,
——, -4 (very overwhelmed) to +4 (very
much in control). In Panel B, Activity increase
is plotted relative to weekly level of Energy: 
- - -, -4 (very tired) to +4 (very energetic).
The Activity and Control relationship was best
fit with a linear equation (p < 0.0001); the
Activity and Energy relationship was best fit
with a step function plus a very small linear
component (p < 0.0001). The step is at week 30.
Thus, activity increased linearly as a function of
feeling in control (Panel A). Energy level
lagged behind then jumped up (panel B), likely
as a result of the motivated exertion depicted in
Panel A.