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ORIGINAL ARTICLE
Year : 2020  |  Volume : 9  |  Issue : 7  |  Page : 3508-3513

Poststroke depression among stroke survivors in Sub-Himalayan region


1 Assistant Professor, College of Nursing, Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India
2 PhD Scholar, College of Nursing, Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India
3 Additional Professor, Department of Neurology, Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India
4 Assistant Professor, Department of Neurology, Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India
5 Assistant Professor, Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India

Correspondence Address:
Dr. Rajesh Kumar
Assistant Professor, College of Nursing, All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand - 249 203
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jfmpc.jfmpc_444_20

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Introduction: Stroke is a leading cause of long-term disability and loss of productive life in developing countries, including India. Ischemic stroke accounts for 85% of all types of stroke with a prevalence of 5%–15% among acute stroke incidents. The prevalence of poststroke depression among acute stroke survivors is varied from 5 to 54%. The study focused on depression among stroke survivors who actively involved in a home-based rehabilitation. Materials and Methods: A descriptive cross-sectional survey was conducted by enrolling 138 stroke survivors consecutively at tertiary care public hospital, North India. A sociodemographic and clinical profile sheet was used to seek information on personal and clinical variables. Information on disability, depression, performance in the activity of daily living, and degree of stroke severity was ascertained by using the Modified Rankin Scale (MRS), Physical Health Questionnaire (PHQ-9), Barthel Index, and National Institutes of Health Stroke (NIHSS). After binary logistic regression model, a multivariate logistic regression was applied to detect the independent predictor of depression. Results: Over 86% (119) of the stroke survivors had no symptoms of depression, and only 14% (19) were reported to have symptoms of depression. Poststroke depression found significant association with disability (P = 0.029) and functional independence (P = 0.0001). A significant difference was observed in the gender (P = 0.018), types of stroke (P = 0.0001), and location of lesion (P = 0.0001) with depression. Binary logistic regression model shows that disability (MRS) status of stroke survivor (P < 0.0001; 95% CI 1.998–2.638) and functional independence (BI) (P < 0.0001; 95% CI –0.034–0.020) are same as independent predictors for depression. Conclusion: Clinician should use the community reintegration, referral, and mandatory screening of the stroke survivors at follow-up visit to rule out the probability of occurrence of poststroke depression.


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