Psychiatric Morbidities After Stroke in Asia: A Systematic Review
Meliza Angelica J. De Leon, Alejandro C. Baroque II
Oct 2023 DOI 10.35460/2546-1621.2023-0021
Introduction
Stroke is currently the second leading cause of death worldwide and is one of the leading causes of long-term disability . [1] In the Philippines alone, it has a prevalence of 0.9%. [2] This is attributed to the shift from communicable diseases, maternal and nutritional causes to noncommunicable diseases due to the increase and aging of the world’s population and decreased death rates in recent years as stated in the Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2015). [1] This emphasizes that although there is a positive trend in survival post-stroke, it also means that there are more individuals who will have to live with the consequences of the disease such as disabilities that affect their quality of life. A significant proportion of the aforementioned disability is attributed to the individuals’ reduced mobility due to hemiparesis, but aphasia and depression have likewise been identified as contributors to the overall burden. [1]
Mood disorders are prevalent after stroke and may hinder physical, functional and cognitive recovery; hence it is undeniably necessary to recognize them early. [3] Post-stroke depression, seen under the scope of Depressive Disorder due to Another Medical Condition in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM V-TR), is the most common psychiatric problem encountered in stroke survivors and is seen in one-third of the cases with a cumulative incidence of 55%. [4-6]
Sixty percent of the world’s population is found in Asia and most of the countries therein are in economic transition. [1,7] Socioeconomic status is a major contributor to stroke burden as greater odds of disability are found in patients with lower educational status and income. [1] Due to disparities in healthcare provision, a tremendous challenge is posed to the control of disease in this part of the world. [7] The Philippine data demonstrated this tremendous burden as health care being largely private and the cost borne out-of-pocket by patients and their families. [2] The delivery of adequate support to rural communities and underprivileged sectors poses additional hurdles. [2] It is of note that stroke mortality is generally higher in this continent when compared to Western Europe, the Americas or Australasia. [7]
Post-stroke depression is the most common psychiatric problem encountered in stroke survivors; however, it is not the only psychiatric morbidity that exists in this population. As previously mentioned, it is impeccable to identify these conditions because they increase the individual’s risk for suboptimal recovery in view of the fact that it affects their ability to engage in rehabilitation therapies. This study aims to identify the psychiatric morbidities frequently recognized after stroke in Asia. This document will review the existing literature on this topic with the goal of increasing awareness and subsequent screening for earlier identification and intervention in this subgroup of survivors.
Methodology
Study Design
This systematic review made use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards and guidelines.
Search Strategy
The following databases were utilized for extensive literature search: PubMed (January 2002 to June 2022), Cochrane Library (January 2002 to June 2022), and EBSCO (January 2002 to June 2022). The search made use of keyword combinations, Boolean operators "AND" and "OR," truncations, and field tags last October 2022. A comprehensive search strategy was utilized: prevalence and post-stroke, and depression and (anxiety or mania or psychosis), and Asia . The search strategy was adapted for each database in order to achieve more sensitivity. The references of relevant publications found by the search were screened for further studies.
The articles included were based on predefined criteria . Cross-sectional studies that discussed stroke survivors who developed post-stroke psychiatric morbidities such as depression, anxiety, mania and psychosis were reviewed . Additional inclusion criteria consisted of studies that have to be written in the English language and having free full texts available . In addition, the geographical area, particularly Asia, had to be reported. Finally, the demographics of patients should be described. The population of interest was post-stroke patients, male and female, aged more than 18 years old.
Quality Assessment
The JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data was used in the assessment for the quality of the articles to be included in this systematic review. This questionnaire consisted of nine questions answerable by yes, no, unclear or not/applicable. The diagram below shows the aforementioned document. Based on the criteria listed, the quality score for the prevalence study is given.
Author | Criteria and corresponding scores |
Total |
% | ||||||||
#1 | #2 | #3 | #4 | #5 | #6 | #7 | #8 | #9 |
Figure 1: JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data
Data Extraction
Two independent researchers were used in the extraction of data presented in this article. A pre-designed Excel worksheet was utilized in the gathering of applicable data. The following information was extracted from the documents selected: authors, year of publication and demographics. The authors also drew out the conditions identified, scales utilized, risk factors, results and conclusions made. Analysis of collected data was done to guarantee consistency. In the event of a dispute, a resolution was made with the help of a third party.
Author | Criteria and corresponding scores |
Total |
% | ||||||||
#1 | #2 | #3 | #4 | #5 | #6 | #7 | #8 | #9 | |||
Ahmed ZM, Khalil MF, Kohail AM, Eldesouky IF, Elkady A, Shuaib A. | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 100 |
Ayasrah SM, Ahmad MM, Basheti IA. | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 100 |
Meng G, Ma X, Li L, Tan Y, Liu X, Liu X, Zhao Y. | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 100 |
Raju RS, Sarma PS, Pandian JD. | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 100 |
Tang WK, Ungvari GS, Chiu HF, Sze KH, Woo J, Kay R. | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 88 |
Table 1: JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data [8]
Results
Study Selection
From the electronic databases used in the study strategy, PubMed yielded 13 results, zero (0) from Cochrane Library and zero (0) from EBSCO. Out of the 13 studies in PubMed, seven articles were identified. Among these, two were excluded because they did not discuss post-stroke psychiatric morbidities but focused on psychosocial problems, quality of life and functional independence. A total of five articles fulfilled the inclusion criteria listed and were used in this systematic review. The flow chart below demonstrates the study selection process. The PRISMA flow chart below shows the study selection process.
Figure 2: PRISMA Flow Diagram
Study Characteristics
The extracted data included the author, publication year, demographics, condition, assessment scales used, risk factors identified and results.
Author | Publication Year | Study Site | Demographics | Condition | Assessment Scales Used | Risk Factors | Results |
Ahmed ZM, Khalil MF, Kohail AM, Eldesouky IF, Elkady A, Shuaib A. | 2020 | Saudi Arabia | Age: 56.72 ± 11.83 Gender: 56% males, NIHSS: 7.60 ± 3.92, MSPSS: 5.40 ± 1.17, mRS: 1.64 ± 1.19, TSH: 2.48 ± 2.61, MMSE: 26.64 ± 1.37 | Post-stroke Depression (PSD) and Post-stroke Anxiety (PSA) | Hospital Anxiety and Depression Scale (HADS) | Higher NIHSS scores, lower MSPSS; higher mRS and discontinuation of rehabilitation. | Clinically significant PSD was found in 36%, while PSA in 32%. PSD was associated with higher NIHSS; lower MSPSS; higher mRS and discontinuation of rehabilitation. PSA was associated with higher TSH; lower MSPSS; while discontinuation of rehabilitation was related to less PSA. NIHSS and MSPSS score were associated with PSD; while PSA was related to TSH level and discontinuation of rehabilitation.
|
Ayasrah SM, Ahmad MM, Basheti IA. | 2018 | Jordan | Age: 56.62 years (SD = 14.2) Gender: 53% males, 47% females, HDS: 11-21
| Post-stroke Depression | Validated hospital depression subscale (HDS) of the Hospital Anxiety and Depression scale. | Low level of education, having a preparatory level of education, having comorbid chronic diseases, inability to perform daily activities by themselves, and patients with comorbid dysphasia. | Post-stroke depression is a significant health problem among Jordanian patients with stroke and warrants serious attention. Clinicians need to consider these important predictors when assessing and managing depression among patients at risk. Factors that correspondingly predicted higher depression categories were low level of education, having a preparatory level of education, having comorbid chronic diseases, patients who reported inability to perform daily activities by themselves, and patients with comorbid dysphasia. |
Meng G, Ma X, Li L, Tan Y, Liu X, Liu X, Zhao Y. | 2017 | China | Age: 69.4 years (range 50–86 years); Gender: 51.8% males. Co-morbidities: 71.1% had a history of hypertension, 45.8% had diabetes mellitus, and 15.7% had atrial fibrillation. | Post-stroke Depression | NIHSS, HAM-A, HAM-D, MMSE | Higher NIHSS scores, higher HAMD scores, lower DA level, lower 5-HT level, higher tumor necrosis factor-α level, and lower NGF level.
| The identification of higher NIHSS scores, higher HAMD scores, lower dopamine level, lower 5-hydroxytryptamine level, higher tumor necrosis factor-α level, and lower nerve growth factor level might be useful for clinicians in recognizing and treating depression in patients after a stroke. |
Raju RS, Sarma PS, Pandian JD. | 2010 | India | Age: 54.3 ± 12.9 years (range, 21–88 years); Gender: 69.8% males
| Post-stroke Depression (PSD) and Post-stroke Anxiety (PSA) | WHOQoL, HADS, FIM | Poor stroke outcome (mRS ≥ 2), older age, severe stroke (NIHSS 2.16 ± 2.1 (median 1, range 0–10) | Presence of anxiety, depression and functional dependence (low FIM scores) were associated with impaired QoL. Older age, stroke severity and presence of depression resulted in decreased independence. |
Tang WK, Ungvari GS, Chiu HF, Sze KH, Woo J, Kay R. | 2002 | Hong Kong | Age: 71 ± 10 years; Gender: 45% males; 48.1% received no education, 29.8% only 1–6 years of education, 56% married, 33% widowed; 60.5% retired and 19.1% were housewives.
| Post-stroke Depression (PSD) and Post-stroke Anxiety (PSA), Post-stroke Mania and Post-stroke Psychosis
| Mini-Mental State Examination (MMSE) and Structured Clinical Interview for DSM-III-R (SCID-DSM-III-R)
| Sociocultural factors, tendency to deny or somatize psychiatric symptoms and low educational attainment. | The frequency of all depressive disorders was 17.2%. Major depressive episodes, adjustment disorder with depressed mood, dysthymia, and generalized anxiety disorder were diagnosed in 7.6%, 8.2%, 1.3% and 0.6% of the subjects, respectively. |
PSD: Post-stroke Depression; PSA: Post-stroke Anxiety; HADS/ HDS: Hospital Anxiety and Depression Scale; NIHSS: National Institutes of Health Stroke Scale; MSPSS: Multidimensional Scale of Perceived Social Support; MRS: Modified Rankin Scale; TSH: Thyroid Stimulating Hormone; HAM-A: Hamilton Anxiety; HAM-D: Hamilton Depression; MMSE: Mini-mental State Examination; DA: Dopamine; 5-HT: 5-hydroxytryptamine; TNF- α: Tumor necrosis factor-α; NGF: Nerve growth factor; WHOQoL: WHO Quality of Life; FIM: Functional Independence Measure; SCID-DSM-III-R: Structured Clinical Interview for DSM-III-R |
According to the articles reviewed, psychiatric morbidities were more commonly identified in male patients in their middle to late adulthood. Most studies utilized the Hospital Anxiety and Depression Scale (HADS). Aside from the HADS, a few articles made use of the Hamilton Anxiety (HAM-A), Hamilton Depression (HAM-D), Mini-mental State Examination (MMSE) and the Structured Clinical Interview for DSM-III-R (SCID-DSM-III-R) to identify psychiatric morbidities in this population. Higher National Institutes of Health Stroke Scale (NIHSS) scores and poor stroke outcomes (higher scores in the Modified Rankin Scale) were associated with a higher likelihood of developing psychiatric morbidities. Depression and anxiety were the most common findings across the reports. The study by Wai-Kwong Tang and colleagues further found that major depressive episodes, adjustment disorder with depressed mood, dysthymia and generalized anxiety disorder were seen at a frequency of 7.6%, 8.2%, 1.3% and 0.6%, respectively, in the population that they deliberated. No cases of mania or psychosis were identified in their document.
Conclusion
Major depressive episodes, adjustment disorder with depressed mood, dysthymia and generalized anxiety disorder were the common psychiatric morbidities identified post-stroke. The HADS is the typical tool used by the studies reviewed to screen for the presence of post-stroke depression and anxiety. Males in their middle to late adulthood, with higher NIHSS scores and poor stroke outcomes (higher scores in the Modified Rankin Scale) were associated with a higher likelihood of developing psychiatric morbidities.
Limitations and Recommendations
This study was bounded by the limited articles available on the chosen topic. It was recommended to establish a specific time frame for assessing and monitoring for symptoms of psychiatric morbidities in individuals post-stroke. Identification of common lesion locations that may predispose patients to develop the aforementioned disorders may likewise be helpful. Aside from the HADS which is designed to screen for depression and anxiety, additional assessment scales that may identify further psychiatric symptoms, such as mania and psychosis, may be explored to check for additional comorbidities. Family and patient education regarding this consequence of stroke should be highlighted to increase awareness and consciousness about the condition. This would lead to increased rates of reporting, earlier intervention and improved rates of recovery.
Acknowledgments
This work was supported by the University of Santo Tomas Hospital, Department of Neuroscience and Behavioral Medicine. We thank the following for their contribution to the completion of this systematic review: I. N. Gomez, G. C. De Castro and J. L. Galan.
-
Katan M, Luft A. Global Burden of Stroke. Semin Neurol [Internet]. 2018 Apr;38(02):208–11. Available from: http://dx.doi.org/10.1055/s-0038-1649503
-
Navarro JC, Baroque AC II, Lokin JK, Venketasubramanian N. The real stroke burden in the Philippines. International Journal of Stroke [Internet]. 2014 May 20;9(5):640–1. Available from: http://dx.doi.org/10.1111/ijs.12287
-
O’Rourke S, MacHale S, Signorini D, Dennis M. Detecting psychiatric morbidity after stroke. Stroke [Internet]. 1998 May;29(5):980–5. Available from: http://dx.doi.org/10.1161/01.str.29.5.980
-
Villa RF, Ferrari F, Moretti A. Post-stroke depression: Mechanisms and pharmacological treatment. Pharmacology & Therapeutics [Internet]. 2018 Apr;184:131–44. Available from: http://dx.doi.org/10.1016/j.pharmthera.2017.11.005
-
Towfighi A, Ovbiagele B, El Husseini N, Hackett ML, Jorge RE, Kissela BM, et al. Poststroke depression: A scientific statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke [Internet]. 2017 Feb;48(2). Available from: http://dx.doi.org/10.1161/STR.0000000000000113
-
Ha EH, Gantioque R. Treatment of post-stroke depression in young stroke survivors. Stroke Res Ther [Internet]. 2020;4(1). Available from: http://dx.doi.org/10.36648/stroke.4.1.1
-
Venketasubramanian N, Yoon BW, Pandian J, Navarro JC. Stroke epidemiology in South, East, and South-East Asia: A review. J Stroke [Internet]. 2017 Sep 30;19(3):286–94. Available from: http://dx.doi.org/10.5853/jos.2017.00234
-
Briggs Institute J. JBI critical appraisal checklist for studies reporting prevalence data. Adelaide; 2017.
-
Smajlovic D. Strokes in young adults: epidemiology and prevention. VHRM [Internet]. 2015 Feb;157. Available from: http://dx.doi.org/10.2147/VHRM.S53203
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