Effective Tools to Predict Depression in Acute and Subacute Phase of Ischemic Stroke
Publication: The Journal of Neuropsychiatry and Clinical Neurosciences
Abstract
Objective:
Despite the high frequency of depression in the first year following stroke, few studies have predicted risk of depression after the acute and subacute stroke periods. The aim of this study was to identify, in the acute and subacute periods, measures that would predict major depression during the first year after stroke.
Methods:
Study subjects were inpatients with ischemic stroke aged 20–85 years within 6 weeks of onset. Patients were evaluated at baseline and at 3, 6, 9, and 12 months. Patients were diagnosed with major depression using the Structured Clinical Interview for DSM-IV. The severity of depressive symptoms was measured with the Patient Health Questionnaire-9 (PHQ-9) and the Montgomery-Åsberg Depression Rating Scale (MADRS).
Results:
Of the 152 potential patients who met inclusion criteria, 49 had follow-up evaluations; one patient with major depression in the acute and subacute periods was excluded from the analysis. Among the remaining 48 patients, the number of those with major depression during the first year of stroke onset was five (10.4%). Patients who developed major depression had significantly more depressive symptoms in the acute and subacute stroke phase as assessed by both the PHQ-9 and MADRS. Patients with PHQ-9 scores ≥9 in the acute and subacute stroke phases were significantly more likely to develop major depression in a chronic phase of stroke.
Conclusions:
The self-administered PHQ-9 can identify patients in the acute and subacute stroke periods who are at increased risk for developing major depression during the first year after stroke.
Stroke was the third leading cause of mortality in Japan in 2017 (1). In 2019, those over age 65 accounted for 28.4% of the total population in Japan, which ranked first among 201 countries (2, 3).
In large cohorts exceeding 25,000 people, poststroke depression has been found to occur in approximately 30% of survivors during the first year following stroke (4). Depression following stroke has been shown in numerous studies to impair both cognitive and motor recovery as well as increase mortality for as long as 10 years following acute stroke (5–10).
Although several studies have found that antidepressant medications can prevent the development of depression (11, 12), many patients are reluctant to take antidepressants before they are depressed. Thus, methods to predict the risk of developing depression after acute stroke are needed. However, very few studies have tried to identify reliable methods for predicting the development of depression after the acute stroke period.
The present study was designed to examine frequency and risks of major depression after ischemic stroke. We tested the hypothesis that subsyndromal depressive symptoms during the acute and subacute stroke periods would predict the development of major depression during the chronic 1-year period following stroke. The aim of this study, therefore, was to assess the reliability of standardized instruments during the acute and subacute stroke periods to predict patients’ likelihood of developing major depression during the first year chronic stage following stroke.
Methods
Participants
Study subjects were enrolled and followed between July 2014 and March 2019 from inpatients at the Department of Neurology, Tokai University Hospital, with ischemic stroke aged 20–85 years within 6 weeks of onset. Patients were excluded if they had impairment of consciousness, history of dementia, another form of brain injury or aphasia with severe comprehension deficits, or cognitive impairment due to stroke that impaired their ability to understand informed consent or mental status questions. In addition, patients were excluded if they met DSM-IV criteria for alcohol or substance abuse or dependence within the 24 weeks prior to enrollment or if they met DSM-IV criteria for schizophrenia or other psychotic disorders. The patients were examined at initial evaluation (i.e., within 6 weeks of stroke onset) and 3, 6, 9, and 12 months after the ischemic stroke. Depression, cognition, and quality of life were assessed at each of these visits. To predict onset of major depression during the chronic stage of the first year after stroke, patients with major depression in the acute and subacute stroke periods (i.e., within 6 weeks of stroke onset) were excluded from the analysis.
The Institutional Review Board for Clinical Research of the Tokai University School of Medicine approved this study. Written consent was obtained from all enrollees.
Neurological Evaluations
At least two neurologists diagnosed an ischemic stroke based on a complete physical and neurological examination, and MRI brain scans. The severity of the stroke was assessed using the National Institutes of Health Stroke Scale (13).
Assessment for Depression
The patients were examined using the Structured Clinical Interview for DSM-IV (SCID) (14, 15) mood and anxiety disorder section. The diagnosis of major depression developing for the first time after stroke was based on symptoms elicited by the SCID and DSM-IV criteria.
The severity of depressive symptoms was objectively assessed using the Japanese version of the Montgomery-Åsberg Depression Rating Scale (MADRS); it comprises 10 items, each of which is scored on a scale that ranges from 0 to 6 (16, 17). The MADRS has been used widely in clinical double-blind studies to assess the efficacy of various antidepressant therapies in Western countries (18).
The Patient Health Questionnaire (PHQ-9) Japanese version consists of questions about the nine symptom criteria upon which the DSM-IV major depression diagnosis is based (19, 20). The PHQ-9 is a self-administered questionnaire that asks patients to rate their symptoms of depression from 0 to 3 (0=not at all; 3=nearly every day) over the past 2 weeks. Total scores from 1 to 4 are categorized as minimal, from 5 to 9 mild, from 10 to 14 moderate, from 15 to 19 moderately severe, and from 20 to 27 severe (19). The PHQ-9 is widely used throughout the world to screen for depressive disorder and monitor depressive symptoms. The original version of the PHQ-9 has been translated into multiple languages and validated in numerous studies globally (20–22).
Cognitive Assessment
Global cognitive impairment was assessed at all evaluations using the Japanese version of the Mini-Mental State Examination (23, 24). Scores may range from 0 to 30, with lower scores indicating greater impairment. In addition, the Frontal Assessment Battery, developed as a short bedside cognitive and behavioral battery to assess frontal lobe functions, was also administered (25, 26). The Frontal Assessment Battery consists of six items, and the score on each item ranges from 0 to 3. A higher score indicates better frontal lobe performance.
Assessment for Quality of Life
The 36-item Short Form Survey (SF–36) (27) is one of the most widely used generic health survey instruments. The Japanese version of the SF–36 (28–30), which has been demonstrated to address issues of validity and comparability with the English version, was used to evaluate health-related quality of life. The SF–36 health questionnaire generates three scores: a physical component summary, a mental component summary, and a role/social component summary (31). All scores were transformed to fit a norm-based score of 50 and standard deviation of 10, with higher scores indicating better quality of life.
Statistical Analysis
This study used a prospective design. Continuous variables were presented as means and standard deviation according to the diagnosis of depression. Categorical variables were summarized by descriptive statistical methods. Continuous variables were compared using the Mann-Whitney U test, whereas categorical variables were compared using the Fisher’s exact test. For each mental, cognitive, or physical characteristic at baseline, a simple logistic regression model was applied to identify factors that predict the onset of depression (32). For each identified factor, the predictive performance of discrimination was evaluated by calculating area under the receiver operating characteristic curve (AUROC). The AUROC was tested to determine whether it was >0.5. The predictive performance of calibration was evaluated by using the Hosmer-Lemeshow test. Threshold value for each predictive factor was determined considering the values of sensitivity and specificity. In order to evaluate the influence of missing values for each predictive factor, multiple imputation was applied (33). All statistical tests were performed with two-sided significance level of 0.05 using SAS 9.4 (SAS Institute, Cary, N.C.).
Results
Participants
A total of 152 patients met inclusion criteria; of these, 99 refused informed consent. In addition, four withdrew their previously granted consent. To predict patients in the acute and subacute stroke periods who would develop major depression during the chronic period of the first year following stroke, one patient who had a diagnosis of major depression in the acute and subacute phase was excluded from the analysis. The remaining 48 patients were included in the analysis. The number of patients with major depression during the chronic first year after stroke onset was five (10.4%). The mean time from stroke to onset of major depression was 7.2 months. Demographic and clinical characteristics of depressed and nondepressed patients are presented in Table 1. Psychiatric history included previous psychiatric outpatient treatment or use of a psychotropic medication.
| Characteristic | Without depression (total N=43) | With depression (total N=5) | pa | ||
|---|---|---|---|---|---|
| N | % | N | % | ||
| Categorical variables | |||||
| Male | 35 | 81.4 | 2 | 40.0 | 0.0716 |
| Employment | 17 | 39.5 | 1 | 20.0 | 0.6372 |
| Living alone | 3 | 7.0 | 0 | 0.0 | 1.0000 |
| Psychiatric history | 5 | 11.6 | 3 | 60.0 | 0.0272 |
| Coronary artery disease | 8 | 18.6 | 0 | 0.0 | 0.5730 |
| Atrial fibrillation | 8 | 18.6 | 1 | 20.0 | 1.0000 |
| Stroke characteristics | 0.3233 | ||||
| Large-artery atherosclerosis | 4 | 9.3 | 2 | 40.0 | |
| Small-artery occlusion | 18 | 41.9 | 1 | 20.0 | |
| Cardioembolism | 8 | 18.6 | 1 | 20.0 | |
| Other demonstrated cause | 12 | 27.9 | 1 | 20.0 | |
| Undetermined cause | 1 | 2.3 | 0 | 0.0 | |
| Left-side lesions | 21 | 48.8 | 2 | 40.0 | 1.0000 |
| Mean | SD | Mean | SD | ||
| Continuous variables | |||||
| Age (years) | 69.0 | 10.5 | 67.2 | 8.3 | 0.3355 |
| National Institutes of Health Stroke Scale | 3.8 | 4.1 | 4.0 | 5.6 | 0.5167 |
| Systolic blood pressure (mmHg) | 157.6 | 23.6 | 174.8 | 36.8 | 0.3275 |
| Low-density lipoprotein cholesterol (mg/dl) | 123.4 | 30.7 | 145.4 | 33.2 | 0.1613 |
| HbA1c (mg/dl) | 6.1 | 1.3 | 5.7 | 0.6 | 0.8259 |
a
Fisher’s exact test was used for categorical variables, and Mann-Whitney U test was used for continuous variables.
Depressive State, Cognitive and Physical Function, and Quality of Life in a Subacute Stroke Phase
The mental, cognitive, and physical characteristics of patients at baseline are summarized in Table 2. The patients who developed major depression during the first year had significantly higher scores at baseline on the MADRS and PHQ-9.
| Without depression (total N=43) | With depression (total N=5) | ||||
|---|---|---|---|---|---|
| Assessment | Mean | SD | Mean | SD | pb |
| MADRS | 4.5 | 5.6 | 15.0 | 9.9 | 0.0102 |
| PHQ–9 | 2.2 | 3.0 | 8.8 | 4.5 | 0.0056 |
| MMSE | 26.9 | 3.3 | 29.6 | 0.5 | 0.0799 |
| FAB | 12.8 | 3.3 | 14.6 | 1.5 | 0.2338 |
| mRS | 1.6 | 1.4 | 2.0 | 1.6 | 0.5197 |
| SF–36 | |||||
| PCS | 42.7 | 13.5 | 32.8 | 22.7 | 0.2118 |
| MCS | 58.5 | 10.5 | 49.6 | 12.5 | 0.1173 |
| RCS | 44.4 | 15.5 | 32.1 | 23.7 | 0.1725 |
a
FAB=Frontal Assessment Battery, MADRS=Montgomery-Åsberg Depression Rating Scale, MCS=mental component summary, MMSE=Mini-Mental State Examination, mRS=modified Rankin Scale, PHQ–9=Patient Health Questionnaire–9, SF–36=36-item Short Form Survey, PCS=physical component summary, QOL=quality of life, RCS=role-social component summary.
b
Test for odds ratio=1 in simple logistic regression.
Predictive Tools for Depression
The predictive performance of discrimination and calibration for the identified two factors are shown in Table 3. MADRS and PHQ-9 in the subacute stroke phase had good classification ability to discriminate those who developed depression during the first year because the AUROCs were 0.83 and 0.88 (i.e., significantly greater than 0.5 compared with random classification). In addition, the Hosmer-Lemeshow test was nonsignificant.
| Variable | AUROC | 95% CI | pb | Hosmer-Lemeshow test p |
|---|---|---|---|---|
| MADRS | 0.83 | 0.61, 1.00 | 0.0033 | 0.4444 |
| PHQ–9 | 0.88 | 0.69, 1.00 | 0.0001 | 0.1646 |
a
AUROC=Area under the receiver operating characteristic curve, MADRS=Montgomery-Åsberg Depression Rating Scale, PHQ–9=Patient Health Questionnaire–9.
b
Test for AUROC=0.5,
Furthermore, the threshold values were determined to make sensitivity plus specificity maximum. The threshold value of MADRS was 11, and its specificity and sensitivity were 0.881 (37/42) and 0.800 (4/5), respectively. The positive predictive value (PPV) and the negative predictive value (NPV) were 0.444 (4/9) and 0.974 (37/38), respectively. The threshold value of PHQ-9 was 9, and its specificity and sensitivity were 0.921 (35/38) and 0.800 (4/5), respectively. The PPV and NPV were 0.571 (4/7) and 0.972 (35/36), respectively. There was one missing MADRS score and five missing PHQ-9 scores in the nondepressed group. Similar results were obtained by the multiple imputation approach, suggesting little influence of missing values. The Pearson correlation coefficient between MADRS and PHQ-9 was 0.64 (p<0.001).
Discussion
To our knowledge, this is the first study to demonstrate that both the PHQ-9 and MADRS in the acute and subacute phase of ischemic stroke (i.e., within 6 weeks poststroke) were able to predict major depression during the chronic first-year period with an accuracy >80%.
Previous studies have demonstrated the efficacy of antidepressants to prevent the development of depression during the first year after stroke (11) and to decrease the mortality rate for depressed patient up to 5 years after stroke (34). Therefore, one might logically ask why the acute and subacute prediction of major depression during the chronic poststroke period is useful in the clinical setting. Based on our prior randomized studies of antidepressants to treat poststroke depression, we found that eight out of 30 patients randomized to medication refused to take medications due to fear of side effects of medications and/or because they did not feel depressed at that time (35). Thus, a significant number of patients with stroke are resistant to taking medications. The current study, however, demonstrated a clear method to identify stroke patients at high risk for developing major depression in the chronic period after stroke. Clinicians, therefore, may monitor the patients who have increased risk of major depression in the chronic stroke phase.
The only other study that we are aware of to examine risk of future poststroke depression was done by Fuentes et al. (36). This study found that higher scores on the Hamilton Depression Rating Scale (HAM-D) was associated with a three times greater risk of poststroke depression at the 3-month follow-up. However, the HAM-D, similar to the MADRS, is based on a clinical interview that requires a trained clinician.
Among combined studies of 2,769 patients hospitalized for subacute stroke or rehabilitation, 21.6% were diagnosed with major depression (37). Furthermore, approximately 15% of patients who were not depressed at initial assessment developed depression during the first year following stroke (4). In Japan, Kaji et al. (38) examined incident depression among 100 patients at 2 to 5 weeks after onset of stroke using the Mini-International Neuropsychiatric Interview (MINI); they found that the prevalence of major depression was 5%. In addition, a multiple-center study examined incident depression among 373 patients in a subacute-chronic phase of stroke (1 month to 1 year after the onset of stroke) using the MINI, and found that the prevalence of major depression was 9.9% (39). In the current study, the prevalence of patients with major depression in the chronic phase of stroke (7 weeks to 1 year after onset of stroke) was 10.4%. In Japan, the prevalence of poststroke chronic onset major depression may be lower than that in the United States and European countries. Therefore, the PPV and NPV should be carefully interpreted for a different population of interest because the PPV and NPV are highly dependent on the prevalence. For the Japanese stroke patient population, we can interpret that the risk for depression increases from 10% to 57% if the score of PHQ-9 is ≥9. For a different population where the prevalence is higher, the PPV or NPV should be interpreted differently.
The present study had the following limitations that should be acknowledged. First, the number of cases was rather small because only one institution was involved. Second, almost two thirds of the patients who met inclusion criteria declined to sign a consent form and therefore could not be included. The reason why so many patients refused to participate is unclear, but most of the patients in this study lived around the Tokai University Hospital; they might have been afraid that neighbors might discover information about their stroke or depression. In any event, additional patients need to be studied to assess the accuracy of the cut-off scores derived from this study as well as the utility of each of these depression scales.
In conclusion, a PHQ-9 score ≥9 in the acute and subacute phase of stroke was associated with an increased risk of developing major depression during the chronic period of the first year following stroke. The self-administered PHQ-9 may be a beneficial tool to help clinicians to identify patients who are at increased risk of developing depression during the first year after stroke.
Acknowledgments
The authors thank Michiyo Iwamoto, Clinical Trial Center of Tokai University Hospital, and Shino Tsuji, Nursing Division of Tokai University Hospital.
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Information & Authors
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Published In
History
Received: 9 April 2020
Revision received: 23 June 2020
Accepted: 29 July 2020
Published online: 22 October 2020
Published in print: Winter 2021
Keywords
Authors
Competing Interests
Dr. Mikami has received research grant support from Grant-in-Aid for Scientific Research, the Japanese Society for Probiotic Science, Otsuka Pharmaceutical, Shionogi & Co., and Taisho Pharmaceutical; honoraria from Eli Lilly, Meiji Holdings, Miyarisan Pharmaceutical, Otsuka Pharmaceutical, Shionogi & Co., Shire Japan, and Takeda Pharmaceutical; and consulting fees from Otsuka Pharmaceutical and Shionogi & Co. Dr. Orihashi has received consulting fees from the Association of Medical Education and Ethics, Daiichi Sankyo, and Kitasato Clinical Research Center. Dr. Kimoto has received research support from Otsuka Pharmaceutical, Shionogi & Co., and Taisho Pharmaceutical. Dr. Mizuma has received research support from SENSHIN Medical Research Foundation. Dr. Nagata has received research support from Scientific Research and personal fees from Daiichi Sankyo Co., Eisai Co., and Takeda Co. Dr. Yamamoto has received grant support from Eisai Co., Ltd.; grant support and personal fees from Otsuka Pharmaceutical Co., Ltd.; personal fees from Meiji Seika Pharma Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Pfizer Japan Inc., Mitsubishi Tanabe Corporation, Shionogi & Co., Eli Lilly and Company, EPS Holdings, Inc., Grant-in-Aid for Scientific Research. Dr. Takizawa has received research grant support from Scientific Research. Dr. Matsumoto has received research support from Aikou Hospital, Dainippon Sumitomo, Keyaki-no-mori Hospital, Kishi Byoin, KOIKE-YA, Kouzu Hospital, Mental Clinic Yokohama Minatomirai, Otsuka Pharmaceutical, Shionogi & Co., Soushu Hospital, Tanzawa Hospital; and honoraria from Astellas Pharma, Dainippon Sumitomo, Eli Lilly, Eisai, GlaxoSmithKline, Janssen, Meiji Seika Pharma, MSD and Mitsubishi Tanabe Pharma, Novartis Pharma, Otsuka Pharmaceutical, Pfizer, Shionogi & Co., and Yoshitomiyakuhin Corporation. The other authors report no financial relationships with commercial interests.
Funding Information
JSPS KAKENHI Grant Number JP26461774:
Tokai University School of Medicine Research Aid:
Supported by JSPS KAKENHI (grant JP26461774) and Tokai University School of Medicine Research Aid.Metrics & Citations
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