Introduction
Worldwide, strokes are the second leading cause of death, after cardiovascular diseases.1 In France, strokes are the first leading cause of acquired disability in adults,2 leading to more quality of life issues when compared to other vascular diseases, such as myocardial infarction.3 Post-stroke depression (PSD) is affecting one third of stroke survivors, with negative consequences such as higher mortality4 and poor recovery.5
The recent “Stroke early management guideline” from the American Heart
Association and American Stroke Association, briefly mentioned PSD, with
no specific recommendation regarding efficient screening tools,
recommended ways to detect the diagnosis or appropriate treatment
strategies.
Several reviews identified a set of PSD risk factors, stressing the
role of mood-related factors such as previous history of mood disorder,
pathological crying at stroke onset, or family history of depression.4,6–9
Socio–demographic factors and global medical factors were also analysed
with some of them being identified as PSD predictors. However, results
are still discordant.7–9
Cognitive status, at the interface between neurologic damages and
psychiatric symptoms, was analysed as well. Post–stroke cognitive
impairment has been already associated with PSD.4,10–12
Cognitive impairment is also observed independently during major depressive episodes,13 and could be ongoing afterwards. Delayed memory,14 executive functions and attentional skills15 have been shown to be impaired even after reaching clinical remission.16
Executive and attentional dysfunctions are often coupled. Recent
findings have shown that attentional dysfunction could be the primum
movens of all depression-related cognitive impairment.17
Other studies suggested that psychomotor retardation could reflect the «
burden » of past depression as being correlated with the number of
previous depressive episodes.17,18
To our knowledge, there is a lack of studies comparing these
different risk factors, and among them neurocognitive impairments,
assessing their weight in PSD outcome. Some results suggested that
depressive-related symptoms were the most predictive item, but cognitive
impairment was always assessed in a global way.8
We therefore assessed the weight of four different types of risk
factors for PSD. We distinguished those related to psychiatric and
mood-related morbidity, those depending on non-psychiatric
co-morbidities and stroke-related features, the ones related to specific
cognitive impairment – at the interface between neurologic damages and
psychiatric symptoms – and lastly the generic ones such as
socio-demographic features.
Patients and Methods
We conducted a prospective cohort study with consecutive inclusions in a stroke unit, at Sainte-Anne hospital, Paris.
Inclusion and Exclusion Criteria
- Inclusion criteria were (1) age over 18, (2) ischemic or
haemorrhagic stroke within 14 days of stroke onset confirmed by magnetic
resonance imaging or computed tomography scan.
- Exclusion criteria were (1) poor global medical condition precluding
an hour participation in assessments, including hemiparesia (N=35,
10.9%), (2) an impossible follow-up, (3) not a fluent French speaker,
(4) aphasia with a language National Institute of Health Stroke Score
(NIHSS) item ≥2 or a Boston Diagnostic Aphasia Examination <8, (5)
hemineglect according to the bells test, (6) antidepressant taken at the
stroke onset (as studies showed a preventive effect and then a lower
rate of PSD with preventive antidepressant treatment),19
(7) major depressive episode present at the stroke onset (8) adults
under legal protection and pregnancy or breastfeeding. (9) subdural
haematoma, subarachnoid haemorrhage, thrombophlebitis and
post-chirurgical stroke.
Estimated Sample Size
We used the 2.19 odds ratio published in our recent meta-analysis on
risk factors associated with PSD regarding “previous history of
depression” (the most informative marker),8 and a PSD prevalence of 17.7% for PSD according to another recent meta-analysis7
to compute estimated sample size. We estimated that 76 patients were
needed to detect a significant role of such risk factors at the end of
the cohort, with a risk of 5% and a power of 90%. As the tests demand
different skills, we estimated on a preliminary test sample that one
patient out of four would roughly be able to be finally tested, raising
the number of patients to be included to 304.
Demographic Data
The following demographic data were assessed: age, gender, profession, school level, marital status.
Clinical Assessment
Data collection and clinical assessment occurred within 14 days of stroke onset, from patient bedside.
- Stroke characteristics: were assessed including lesion side (right, left, bilateral, median) and stroke severity with the NIHSS.20
- Cognitive tasks: were performed directly from patient bedside, and included the d2 test (sustained and selective attention),21 the Dubois’s 5 words test (verbal memory),22 the clock drawing test (executive functions, spatial organisation),23 and the digit span trial (working memory, verbal memory).24 The test description is available in Supplemental Materials.
- Psychiatric assessment: included the screening of actual and past
depressive episodes with a semi-structured interview (Mini International
Neuropsychiatric Interview, MINI-depression, Fifth edition), depressive
symptoms being assessed with the Beck Depression Inventory.25
Patients were asked for other past psychiatric history (psychiatric
care, treatments). Patients also filled-in the Clinical Global
Impression and the Standardised Assessment of Personality Abbreviated
Scale (SAPAS), a questionnaire of 8 questions to detect personality
disorder. Score ≥3 indicate a personality disorder.26 Alcohol Use Disorders Identification Test (AUDIT-C) was completed: the threshold value is 5 for men and 4 for women.27 Heavy Smoking Index was completed to detect tobacco use disorder (threshold value of 2).28
Three months after the first visit, all patients were called by a
psychiatrist and assessed for depression using DSM criteria with
MINI-depression. The single assessment of depression after 3 months is
based on a previous work, showing that 85% of PSD occurred in the three
months following stroke.29
This study was conducted in accordance with the Declaration of
Helsinki and was approved by the French National Ethics Committee called
“Comité de Protection des Personnes Sud-Méditerranée II” which
reference number is 217 R15. The identification number of the protocol
was 2017-A00339-44. All patients gave written informed consent prior to
participation. All data were recorded anonymously. This study was
registered on clinicaltrials.gov (NTC04008719).
Statistical Analyses
Student t-test was used to compare continuous variables and χ2
test to compare categorical variables. Fisher’s exact test was used
when minimum expected count was not obtained. Initial data were analysed
to study correlation between variables: Pearson correlation was used.
When variables were not normally distributed, Spearman test was used.
Logistic regression was performed to detect in a multivariate way which
parameters were predictive of PSD. For all tests, the threshold of
significance was set at p≤0.05.
Positive Predictive Value (PPV) and Negative Predictive Value (NPV)
of the confirmed predictive factors were calculated. Positive predictive
value (PPV) is the proportion of patients with positive predictors that
will have PSD (PPV = True Positives/[True Positives + False Positive]),
and the negative predictive value (NPV) is the proportion of patients
with negative predictors that will not have PSD (NPV = True
Negatives/[True Negatives + False Negatives]).
All statistical analyses were performed with IBM SPSS Statistics for windows, version 23.0. Armonk, NY:IBM Corp.
Results
Among 321 consecutive stroke patients screened between May 2017 and October 2017, 59 were finally included (Figure 1).
 |
Figure 1 Flow-chart of the study.
|
Comparison Between Included and Excluded Patients
There was no difference between the recruited population compared to
the others regarding gender. However, the included patients were younger
(p<0.001) with a lower level of severity considering NIHSS
(p<0.001).
Sample Characteristics at Baseline
Fifty-three (89.8%) ischaemic strokes were detected, the other being
haemorrhagic. Our sample included 21 (35.6%) women, mean age was 61.9
(SD18.5).
Clinical, imaging characteristics and cognitive tests (Table 1)
were not independent, as the NIHSS, working memory, verbal memory and
age were correlated with some parameters of the d2 Test, and the number
of past depressive episode was correlated with the percentage of d2
mistakes.
 |
Table 1 Sample Characteristics of 59 Patients Hospitalized for a Stroke. There Was No Missing Value
|
Prevalence of PSD, Univariate and Multivariate Analyses
Three months later, two patients could not be assessed. One died (stroke recurrence) and one was lost to follow-up.
PSD was diagnosed in 8 patients (13.6% of total sample), all of them being men.
Univariate analysis (Table 2)
identified four variables associated with PSD: previous history of
depression, previous history of hypertension, tobacco use disorder and
male gender, but none of the cognitive test results. We then analysed
the associated variables in a logistic regression analysis (Table 3)
apart from gender because of the absence of contrast (100% of PSD being
males). Only “previous history of depressive episode” remained a
significant predictive factor, the model explaining 19% of the total
variance (OR=18.0; p=0.002). When considering only male patients, the
model explained 33% of the total variance (OR=42.0; p=0.001).
 |
Table 2 Univariate Approach of
Factors Describing a Sample of 59 Patients with Stroke, According to the
Development (or Not) of a Post-Stroke Depression 3 Months Later
|
 |
Table 3 Logistic Regression
|
Calculated PPV and NPV were, respectively, 46% and 95% for previous
history of depression. When considering only male patients, we obtained
PPV 75% and NPV 93%.
Discussion
In a study analysing 59 consecutive patients hospitalized in a
neurological department specialized in stroke, 14% developed a PSD three
months later. A past history of depression assessed at inclusion was
the only predictive factor of future PSD when using a multivariate
approach, with a positive predictive value of 46% and a negative
predictive value of 95%. Patients with a previous history of depression
had indeed a 10-fold increased risk for PSD. Contrary to our initial
hypothesis, no cognitive test performed at the acute period of the
stroke was predictive of later PSD.
Patients included in our study were significantly younger and
clinically less severe (considering NIHSS) than the rest of the sample.
This is explainable as aphasia and hemiparesia were exclusion criteria
and are distinct NIHSS items. We assume that it is a selection bias,
limiting the generalisation of our results and narrowing its predictive
value to patients that are questionable.
In our sample, depression prevalence three months after stroke is 14%, contrasting with the 30% described in previous studies,4,29 but close to a recent meta-analysis that found a pooled prevalence of PSD of 17.7%.7
Our strict DSM assessment avoided over-estimation, but our method
excluded aphasic and clinically instable patients, leading indeed to
younger, more professionally active patients; therefore, to patients
with a lower risk of developing PSD. Moreover, we chose a single
assessment of PSD after 3 months whereas other studies frequently rely
on a follow-up of 6 months.6
We aimed at identifying predictive factors for PSD and after logistic
regression, only the item “previous history of depression” remained
relevant. The fact that no cognitive test was associated with PSD, could
be due to the small sample size leading to a lack of statistical power
as an association between cognitive impairment and PSD has been already
detected.4 On the other hand, these studies assessed cognitive functions in a global way that did not allow specific predictive features.30,31
Previous history of depression is a simple feature and can be
accurately assessed with brief semi-structured interview, such as the
MINI. Our results stress the need of a systematic interview of patients
with stroke, at the acute phase, to screen and detect unnoticed past
depressive episodes. Previous history of depressive episode is a
well-known risk factor for depressive recurrence.32
Genetic factors as polymorphisms of serotonin transporters confer
vulnerability to depression and have been identified as risk factors for
post-stroke depression.4,33
Stroke could be considered as a biopsychosocial stress leading to
recurrence. Another hypothesis of possible mechanism of the impact of
previous history of depressive episode on PSD, is that previous
depressive episodes have consequences like a possible cognitive scar
that could lead to recurrence.15
Some limits should be stressed in the present study. First, the
recruitment was monocentric and hospital-based, limiting results
generalizability. However, this approach allows a complete recruitment
of all stroke patients comparing with other studies in rehabilitation
units and a relatively low attrition rate was observed in our sample.
Second, we excluded patients with severe stroke, therefore all patients
with significant aphasia, which creates a bias and explains the high
drop-out between patients screening and inclusion. However, as language
is needed to obtain patients’ agreement and is required to understand
the different cognitive tests, such bias is difficult to avoid. Anyhow,
it means that the conclusions drawn from this study have to be limited
to patients able to communicate and to perform cognitive tests. Third,
the sample size remains relatively small and may have lowered
statistical power. Finally, all depressed patients were men, which
constitutes a sample bias and is strikingly not in line with previous
reviews.
Conclusion
We confirm the strength of mood-related risk factors for PSD and
allow the identification of an at-risk sub-group of patients for whom a
specific follow-up monitoring their mood is needed. Further
placebo-controlled trials are needed to recommend preventive
antidepressant for this sub-group. Many studies are involved in
identifying new complex biomarkers, but the fact that a simple clinical
factor, such as past depressive episode, is driving the majority of
predictive factor in the present study could be considered as a positive
result, such factor being relatively easy, quick and costless to
assess.
The authors thank neurologists, nurses, neuropsychologist,
speech-therapist of the neuro-vascular unit, Sainte-Anne Hospital.
Thanks to Amandine Petit, research nurse at the CMME. Thanks to Alexis
Dorra for statistical advice. Raw data are available on request by
mailing the corresponding author.
