Skip to main content
The Egyptian Journal of Neurology, Psychiatry and Neurosurgery
Download PDF

Post-stroke depression: frequency, risk factors, and impact on quality of life among 103 stroke patients—hospital-based study

The Egyptian Journal of Neurology, Psychiatry and Neurosurgery volume 56, Article number: 66 (2020) Cite this article

Abstract

Background

Post-stroke depression (PSD) has worse functional outcomes and quality of life. Despite the extensive literature on this topic, there is no agreement on the frequency or risk factors for post-stroke depression.

Objectives

To establish the frequency and risk factors of post-stroke depression and its impact on quality of life.

Patients and methods

One hundred three stroke patients were recruited from the out-patient clinic of Qena University Hospital who satisfied the WHO definition for stroke, together with a control group of 50 age- and sex-matched healthy volunteers. A complete history, neurological examination, and CT brain were obtained for each patient. DSM-IV TR criteria were used for diagnosis of depressive disorders which was scored with the Hamilton depression rating scale (HAM-D); Barthel Index (BI), and quality of life were also measured.

Results

Thirty-eight (36.9%) stroke patients had PSD which was significantly higher than in the normal population (control group 12%). Statistically significant risk factors for PSD included low educational level, low socioeconomic status, smoking, and post-stroke functional impairment. Post-stroke depression has an impact on quality of life.

Conclusion

Post-stroke depression is a relatively common complication of stroke and can affect the quality of life. Low educational level and socioeconomic status, as well as smoking and functional impairments, were considered as risk factors for the occurrence of post-stroke depression. Early detection of predictors of post-stroke depression may improve the outcome of stroke and prevent the psychiatric consequences.

Introduction

Stroke is an important neurological problem and a leading cause of death in clinical practice. Among survivors, over half have significant physical disabilities and/or psychiatric complications, the most common of which is post-stroke depression (PSD). In 2017, stroke made up the third-leading cause of disability-adjusted life-years (DALYs) worldwide [1]. The prevalence of stroke in a study conducted in our community (Qena governorate) was 922 in 100,000 [2]. Martin Roth was the first to study the association between depression and stroke [3]. Later, Folstein reported that depression was more common in stroke patients than in patients with a similar level of motor disability caused by orthopedic problems [4]. Various reports have shown a significant association between depression and quality of life in stroke survivors [5, 6]. The double burden of stroke and depression has been considered the main leading cause to total years lost to disability based on the global burden of disease report [1]. A reciprocal relationship between the severity of initially diagnosed PSD and stroke recovery outcome has been noted in many studies [7, 8], with increased mortality rates [9,10,11], and improved survival and quality of life with antidepressant medications and psychoeducation [12,13,14,15,16]. Across the literature, there is great variability of PSD frequency; two recent Nigerian studies have found PSD at 22.9% and 42.9%, respectively [17, 18], and another Tanzanian study found PSD to be 30% [19]. In a recent systematic review of post-stroke depression in the Middle East and North Africa reported that the prevalence ranged from 17 to 73% [20].

In fact, the previous studies showed that the frequency of PSD is influenced by patient’s selection, socioeconomic state, educational level, severity of stroke, location of the lesion, study design, time of assessment after stroke, and the associated risk factors.

Unfortunately, PSD is often underdiagnosed and under-reported, in part because cognitive problems after stroke can confound the symptoms of depression and make the diagnosis of depression difficult. Despite increased interest in the socioeconomic aspects of chronic medical conditions in developing countries, there is little information about PSD in Egypt. To address this point, our study is aimed to estimate the frequency of PSD, associated risk factors, and impact on quality of life (QoL) among stroke patients in Qena University Hospital (upper Egypt).

Patients and methods

In this cross-sectional study, we recruited 103 (out of 180) patients with stroke from the neurology outpatient clinic of Qena University Hospital from September 2014 to August 2015; they were compared with a group of 50 age- and sex-matched healthy control subjects that were recruited from 2nd-degree relatives of patients. Qena is one of the southern governorates of Egypt. Inclusion criteria included patients diagnosed with stroke according to the WHO definition as a syndrome of rapidly developing clinical signs of focal or global disturbance of cerebral function, with symptoms lasting 24 h or longer with no apparent cause other than of vascular origin [21], and stroke diagnosis was confirmed by computerizing tomography of the brain (CT scan) The duration of stroke was the time passed since the onset of stroke to the time of examination (ranging from the onset of stroke up to 2 years). They were 18 years or older; alert; oriented with persons, time, and place; had no problems in communication; willing to participate in the study; and able to give written informed consent.

Stroke patients were classified according to the side of the lesion to right and left hemisphere and according to the location of the lesion to frontal and non-frontal as the frontal region has the greatest vulnerability to post-stroke mood disorder [22].

Exclusion criteria included individuals who were unable to communicate due to a disturbed level of consciousness. Severe global dysphasia was excluded on the bases of clinical assessment that interferes with patients’ life and communication. Severe cognitive impairment (as assessed by Mini-Mental State Examination [MMSE] which was used to exclude patients with score < 18 for literate and < 16 for illiterate subjects [23, 24]) as cognitive problems after stroke can confound the symptoms of depression and make the diagnosis of depression difficult, and severe hearing or visual impairment that affect the communication and assessment of depression. Severe medical complications (renal or liver failure as these are confounding factors associated with depression) were also excluded. Neither the patient nor controls were on antidepressant medications.

Structured Clinical Interview for DSM-IV-Clinician Version (SCID-CV) [25] the Arabic version [26] was used for the diagnosis of depression and exclusion of other psychiatric comorbidities in patients and controls. It contains seven diagnostic modules for axis I disorders.

Socioeconomic status was assessed with an appropriate Arabic validated scale, as it was classified into low, middle, and high socioeconomic status based on the subject score [27]. It consists of 4 dimensions: parents’ level of education, parents’ occupation, total family monthly income, and lifestyle of the family. Each item was given a score of 1. According to the total score, the socioeconomic level was divided into three categories: high (85–100%), moderate (60–84%), and low (< 60%).

The residence of each patient or control subject is classified as a rural or urban resident according to the geographical distribution of rural (from the village) and urban (from city) areas location in Qena governorate. Clinical characteristics and risk factors were recorded for each patient. Hamilton depression rating scale (HAM-D) [28] was used to measure the severity of depressive symptoms according to the subject score as follows: 0–7 = normal, 8–13 = mild depression, 14–18 = moderate depression, 19–22 = severe depression, and > 23 = very severe depression. The World Health Organization Quality of Life (WHOQOL)-BREF [29] and Barthel Index (BI) [30] were used to measure quality of life and functional status of stroke patients.

All participants provided an informed written consent. The local Ethical Committee of Assiut University Hospital approved the study.

Statistical analysis

The data were analyzed using the Statistical Package for Social Science (SPSS Inc., 2008, 233 South Wacker Drive, Chicago, IL, USA) version 17.0 software.

The sampled population was divided into diagnostic groups of depressed and non-depressed individuals. The chi-square test was used to find the significance of study parameters on categorical variables, while the Mann-Whitney U test was used to analyze continuous variables (they were not normally distributed) between the two groups. The P value was set at 0.05. Independent predictors of depression were determined by binary logistic regression. A P value of less than 0.05 was considered significant.

Results

A significantly higher relative frequency of depression was detected among stroke patients compared with the control group (P < 001). Thirty-eight patients (36.9%) had depression, of whom 22 (21.4%) had major and 16 (15.5%) patients had minor depressive disorder; 6 out of 50 (12%) individuals in the control group had depression (Table 1). Patients also had a significantly higher HAM-D score (8.6 ± 5.8) than the control group (5.2 + 4.2) (P < 0.001). Post-stroke depression was significantly associated with low educational level, low socioeconomic status, and smoking, while age, gender, residence, marital, and job status were not significantly different between depressed and non-depressed stroke patients (Table 2). There were no significant differences between depressed and non-depressed stroke patients in symptoms of hypertension, cardiac disease, or diabetes mellitus. In addition, there was no significant association with a past psychiatric history of depression or family history of depression in first-degree relatives (Table 3).

Table 1 Demographic, socioeconomic, medical, and psychiatric risk factors in stroke patients and control subjects
Full size table
Table 2 Demographic and socioeconomic data for post-stroke depression
Full size table
Table 3 Comorbid medical and psychiatric illness and post-stroke depression
Full size table

There were no significant relationships between the various stroke indices and PSD except for functional impairment (measured according to Barthel Index scale), which was significantly higher in the patients with post-stroke depression (Table 4). Physical, psychological, and environmental QOL assessed by WHOQOL-BREF questionnaire was significantly worse among stroke patients with depression than in stroke patients without depression (Table 5).

Table 4 Stroke indices and post-stroke depression
Full size table
Table 5 Quality of life and state of functioning among stroke patients groups (with versus without depression)
Full size table

Discussion

The main findings of the present study were the relatively high frequency of PSD of 36.9%, low educational level, low socioeconomic status, smoking, and functional impairment as measured by BI scale and were all considered risk factors associated with PSD, while other risk factors had no relationship with PST. PSD has a worse impact on physical, psychological, and environmental QOL

Two possibilities for the occurrence of PSD are the following: firstly, PSD is a result of damage of a certain brain region and presumably subsequent changes in neurotransmitters such as serotonin and dopamine, and secondly, it may be a psychological reaction to the disabilities sequelae resulting from a stroke that affects the quality of life.

The prevalence of PSD has been summarized in numerous individual studies and meta-analyses and was estimated to be in the range of 20 to 65% [31]. Another two meta-analyses estimated the prevalence at 29% (20,293 patients) in 43 studies over a period of 5 years post-stroke [32] and 31% (25,488 patients) in 61 prospective studies over 5 years post-stroke [33]. In the current study, depression was diagnosed in about 37% of patients. Differences in prevalence estimates are probably related to the variation in the clinical presentation of stroke and the difficulty of evaluating depression in many cases [34] or to the use of different measures and diagnostic criteria for diagnosis [35]. Another factor related to the difference in the frequency of PSD is the small sample size as local studies with sample sizes of less than 100 patients for PSD reported a prevalence of 30% or less. It is possible that the small samples were not sufficient to give the studies the required power to address the hypothesis, which may be responsible for the lower prevalence reported.

Most (21.4%) of our patients had major depressive disorders( MDD) while 15.5% had a minor depressive disorder. This is similar to figures of 19.9% and 12.6% from Mitchell and colleagues [36].

Gender and age did not reveal any significant association with PSD despite the fact that depressive disorders are more prevalent among females in the general population. This is consistent with two previous systematic reviews: De Ryck and colleagues [31] reported that gender was not a risk factor for PSD in 13 out of 21 studies, while age was not a predictor in 16 studies. A similar conclusion was reached by Kutlubaev and Hackett [37] reviewing 23 studies that included 18,374 stroke patients from 23 studies. However, not all studies find the same relationship with aging. There was a high prevalence among older stroke patients in a study carried out in Jordan [38], while there was increased prevalence among younger stroke patients in other studies [39, 40].

We found that the lower the educational level, the higher the prevalence of PSD, a finding that is consistent with numerous previous studies [39, 41,42,43]. This may be due to defective coping strategies and a less consistent premorbid support system in less educated subjects. The significant association of PSD with smoking was also consistent with previous findings [38, 44], which may be explained by deficient vitamin D in smokers according to Ren and colleagues [44] and the superadded dysphoric effect of sudden nicotine abstinence, withdrawal mood symptoms, and craving.

The absence of a significant association between PSD and hypertension, diabetes, or cardiac disease was partly consistent with some previous reports [31, 37, 45] which found that hypertension and hyperlipidemia were not associated with PSD, while diabetes mellitus was identified as a predictor. Contrary to the present findings, a past history of depression [31, 37] and family history of depression were also significantly correlated to PSD [36].

In the current study, PSD was more common in those with more severe post-stroke functional impairments as measured by the Barthel Index that is in line with Schöttke and colleagues [46]. Thus, the burden of functional impairment of stroke can increase the risk of PSD, which then leads to further impairment like increased disability, reduced social activities, delayed recovery, failure to return to work, and longer institutional care and so affect quality of life.

In the present study, there was no significant relationship between the duration since onset of stroke and the frequency of PSD. Previous studies reported an increased frequency of depression early after stroke [38, 47]. However, since this recovered gradually with improvement of physical symptoms and restoration of a normal quality of life, it seems likely that it is quality of life rather than the time after stroke that determines the severity of PSD [48]. In confirmation of our findings, the type of stroke (ischemic vs. hemorrhagic) was not found to be a predictor in many studies [ 31, 37].

The relationship between PSD and lesion location is a matter of some debate. In the present study, there was no significant relationship between PSD and lesion location consisting with Nickel and Thomalla meta-analysis, 2017 [49], and Wei and colleagues, [50] as they concluded that there is no clear pattern as to the association of stroke lesion location and PSD. However, few reports found a significant correlation with left frontal and left basal ganglionic lesions and/or the proximity of the ischemic lesion to the frontal pole [51]. Others find this correlation with the right hemisphere especially the frontal lobe [40, 52]. The absence of a relationship between lesion location and PSD could be largely due to exclusion criteria used in the present study as we excluded patients with severe aphasia (left hemispheric affection), and patients with cognitive impairment that makes difficult communication with the patient and affects the assessment of depression which is one of our limitation of the study.

Limitation of the study

Main limitations of this study are the relatively small sample size and the highly selective patient criteria, which may be required for accurate determination of depression, but it limits the interpretation of the frequency of PSD; lack of MRI study in some cases to measure brain lesion; and follow-up of these patients on antidepressant medication.

Conclusion

PSD is a frequent complication of stroke and can affect the quality of life. Low educational level and socioeconomic status, as well as smoking and functional status of stroke, were predictors for the development of PSD. PSD has a worse impact on the quality of life. A comprehensive evaluation and management of PSD improves the outcome of stroke. Further studies that involve the best treatment approaches for such patients are urgently required.

Availability of data and materials

The data supporting the results reported in the article is already saved and available on request at any time.

Abbreviations

PSD:

Post-stroke depression

WHO:

World Health Organization

DALYs:

Disability-adjusted life-years

DSM-IV- TR:

Diagnostic and statistical manual of mental disorders 4th edition revised

HAM-D:

Hamilton depression rating scale

BI:

Barthel Index

QoL:

Quality of life

MMSE:

Mini-Mental State Examination

WHOQOL-BREF questionnaire:

The World Health Organization Quality of Life

MDD:

Major depressive disorders

References

  1. GBD 2017 DALYs and HALE Collaborators. Global, regional, and national disability adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1859–1922.

  2. Khedr EM, Fawi G, Abdela M, Mohammed TA, Ahmed MA, El-Fetoh NA. and ZakiAF.Prevalence of ischemic and hemorrhagic strokes in Qena Governorate, Egypt: community-based study. J Stroke Cerebrovasc Dis. 2014;23(7):1843–8.

    PubMed  Google Scholar 

  3. Roth M. The natural history of mental disorder in old age. J Ment Sci. 1955 Apr;101(423):281–301.

    CAS  PubMed  Google Scholar 

  4. Folstein MF, Maiberger R, McHugh PR. Mood disorder as a specific complication of stroke. J Neurol Neurosurg Psychiatry. 1977 Oct;40(10):1018–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Gbiri CA, Akinpelu AO. Quality of life in Nigerian stroke survivors during the first 12 months post stroke. Hong Kong Physiother J. 2012;30(1):18–24.

    Google Scholar 

  6. Abubakar SA, Isezuo SA. Health related quality of life of stroke survivors: experience of a stroke unit. Int J Biomed Sci. 2012;8(3):183–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Robinson RG, Jorge RE. Post-stroke depression: a review. Am J Psychiatry. 2016;173:221–31.

    PubMed  Google Scholar 

  8. Blöchl M, Meissner S, Nestler S. Does depression after stroke negatively influence physical disability? A systematic review and meta-analysis of longitudinal studies. J Affect Disord. 2019;247:45–56.

    PubMed  Google Scholar 

  9. Stein LA, Goldmann E, ZamzamA LJM, Messé SR, Cucchiara BL, et al. Association between anxiety, depression, and post-traumatic stress disorder and outcomes after ischemic stroke. Front Neurol. 2018;9:1–9.

    Google Scholar 

  10. Bartoli F, Di Brita C, Crocamo C, Clerici M, Carra G. Early post-stroke depression and mortality: meta-analysis and meta-regression. Front. Psychiatry. 2018;9:530.

    PubMed  PubMed Central  Google Scholar 

  11. Cai W, Mueller C. Li Y-Jing, Shen W-Dong, Stewart R. Post stroke depression and risk of stroke recurrence and mortality: a systematic review and meta-analysis, Ageing Res Rev. 2019;50:102–9.

    Google Scholar 

  12. Kraglund KL, Mortensen JK, Grove EL, Johnsen SP, Andersen G. TALOS: a multicenter, randomized, double-blind, placebo-controlled trial to test the effects of citalopram in patients with acute stroke. Int J Stroke. 2015;10:985–7.

    PubMed  Google Scholar 

  13. Mead GE, Hsieh CF, Hackett M. Selective serotonin reuptake inhibitors for stroke recovery. JAMA. 2013;310:1066–7.

    CAS  PubMed  Google Scholar 

  14. Hackett ML, Köhler S, O’Brien JT, Gillian E. Mead: Neuropsychiatric outcomes of stroke. Lancet Neurol. 2014;13:525–34.

    PubMed  Google Scholar 

  15. Yejin Lee, Brian Chen, Mandy W.M. Fong and Alex W.K. Wong: The effect of therapeutic interventions on post-stroke depression: a systematic review and meta-analysis. Arch Phys Med Rehabil;2018: 99, : e220-e221.

  16. Causes GBD. of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1151–210.

    Google Scholar 

  17. Oni OD, Olagunju AT, Olisah VO, Aina OF, Ojini FI. Post-stroke depression: prevalence, associated factors and impact on quality of life among outpatients in a Nigerian hospital. S Afr J Psychiat. 2018;24(0); a1058.

  18. Olibamoyo O, Adewuya A, Ola B, Coker O, Atilola O. Prevalence and correlates of depression among Nigerian stroke survivors. S Afr J Psychiat. 2019;25(0), a1252.

  19. Saadi A, Okeng’o K, Biseko MR, Shayo AF, Mmbando TN, Grundy SJ, et al . Post-stroke social networks, depressive symptoms, and disability in Tanzania: a prospective study: Int J Stroke. 2018 October ; 13(8): 840–848.

  20. Kaadan MI, Larson MJ. Management of post-stroke depression in the Middle East and North Africa: too little is known. Neurol Sci. 2017;15(378):220–4.

    Google Scholar 

  21. Wolf PA, Kannel WB, Dawber TR. Prospective investigations: the Framingham study and the epidemiology of stroke. Adv. Neurol. 1978;19:107–20.

    CAS  PubMed  Google Scholar 

  22. van Zandvoort MJ, Nys GM, van der Worp HB, de Haan EH, de Kort PL and Kappelle LJ. Early depressive symptoms after stroke: neuropsychological correlates and lesion characteristics. J Neurol Sci. 2005; Jan 15; 228(1):27-33.

  23. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.

    CAS  PubMed  Google Scholar 

  24. Farrag A, Farwiz HM, Khedr EH, Mahfouz RM, Omran SM. Prevalence of Alzheimer’s disease and other dementing disorders: Assiut-Upper Egypt study. Dement Geriatr Cogn Dis. 1998;9(6):323–8.

    CAS  Google Scholar 

  25. First MB, Spitzer RL, Gibbon M, Williams JBW, Benjamin LS. Structured Clinical Interview for DSM-IV-clinician version (SCID-CV) (user’s guide interview). Washington, DC: American Psychiatric Press; 1997.

    Google Scholar 

  26. El Missiry A, Sorour A, Sadek A, Fahy T, Abdel Mawgoud M, Asaad T. Homicide and psychiatric illness: an Egyptian study [MD thesis]. Cairo: Faculty of Medicine, Ain Shams University; 2004.

    Google Scholar 

  27. Abd El-Tawab AA. Family socio-economic status scale. Journal of Faculty of Education, Assiut University. 2012;28(1).

  28. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960 Feb;23:56–62.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Skevington SM, Lotfy M. O'Connell KA; WHOQOL Group. The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual Life Res. 2004 Mar;13(2):299–310.

    CAS  PubMed  Google Scholar 

  30. Mahoney FI, Barthel D. Functional evaluation: the Barthel Index. Md State Med J. 1965 Feb;14:61–5.

    CAS  PubMed  Google Scholar 

  31. De Ryck A, Brouns R, Geurden M, Elseviers M, De Deyn P, Engelborghs S. Risk factors for poststroke depression: identification of inconsistencies based on a systematic review. J Geriatr Psychiatry Neurol. 2014;27(3):147–58.

    PubMed  Google Scholar 

  32. Ayerbe L, Ayis S, Wolfe CD, Rudd AG. Natural history, predictors and outcomes of depression after stroke: systematic review and meta-analysis. Br J Psychiatry. 2013 Jan;202(1):14–21.

    PubMed  Google Scholar 

  33. Hackett ML, Pickles K. Part I. frequency of depression after stroke: an updated systematic review and meta-analysis of observational studies. Int J Stroke. 2014 Dec;9(8):1017-1025.

  34. Townend E, Tinson D, Kwan J, Sharpe M. ‘Feeling sad and useless’: an investigation into personal acceptance of disability and its association with depression following stroke. Clin Rehabil. 2010 Jun;24(6):555–64.

    PubMed  Google Scholar 

  35. Bartoli F, Lillia N, Lax A, Crocamo C, Mantero V, Carrà G, et al. Depression after stroke and risk of mortality: a systematic review and meta analysis. Stroke Res. Treat. 2013;2013:862978.

    PubMed  PubMed Central  Google Scholar 

  36. Mitchell AJ, Sheth B, John Gill, Yadegarfar M, Stubbs B, Mohammad Yadegarfar et al . Prevalence and predictors of post-stroke mood disorders: A meta-analysis and meta-regression of depression, anxiety and adjustment disorder:Gen Hosp Psychiatry .2017 ; 47:48-60.

  37. Kutlubaev MA, Hackett ML. Part II: predictors of depression after stroke and impact of depression on stroke outcome: an updated systematic review of observational studies. Int J Stroke. 2014 Dec;9(8):1026–36.

    PubMed  Google Scholar 

  38. Ayasrah SM, Ahmad MM, Basheti IA. Post stroke depression in Jordan: prevalence correlates and predictors. J Stroke Cerebrovasc Dis. 2018 May;27(5):1134–42.

    PubMed  Google Scholar 

  39. Karamchandani RR, Vahidy F, Bajgur S, Vu KYT, Choi HA, Hamilton RK, et al. Early depression screening is feasible in hospitalized stroke patients. PLoS One. 2015;10(6):e0128246.

    PubMed  PubMed Central  Google Scholar 

  40. Effat SM, Mohamed MM, El Essawy HI, El Sheikh MM, Abdul Aal HS. Predictors and consequences of post-stroke depression in a sample of Egyptian. Arab J Psychiatry. 2011;22(1):19–26.

    Google Scholar 

  41. Backhouse EV, McHutchison CA, Cvoro V, Shenkin SD, Wardlaw JM . Cognitive ability, education and socioeconomic status in childhood and risk of post-stroke depression in later life: a systematic review and meta-analysis. PLoS ONE:2018 13(7): e0200525.

  42. McHutchison CA, Backhouse EV, Cvoro V, Shenkin SD, Wardlaw JM. Education, socioeconomic status and intelligence in childhood and stroke risk in later life: a meta-analysis. Epidemiology. 2017;28:608–18.

    PubMed  Google Scholar 

  43. Paul N, Das S, Hazra A, Ghosal MK, Ray BK, Banerjee TK, et al. Depression among stroke survivors: a community-based, prospective study from Kolkata. India. Am J Geriatr Psychiatry. 2013 Sep;21(9):821–31.

    PubMed  Google Scholar 

  44. Ren W, Gu Y, Zhu L, Wang L, Chang Y, Yan M, et al. The effect of cigarette smoking on vitamin D level anddepression in male patients with acute ischemic stroke. Compr Psychiatry. 2016;65:9–14.

    PubMed  Google Scholar 

  45. Yang SR, Hua P, Shang XY, Hu R, Mo X, Pan XP. Predictors of early post ischemic stroke apathy and depression: a cross-sectional study. BMC Psychiatry. 2013;13:164.

    PubMed  PubMed Central  Google Scholar 

  46. Schöttke H, Gerke L, Düsing R, Möllmann A. Post-stroke depression and functional impairments – a 3-year prospective study. Compr Psychiatry. 2020;99:152171.

    PubMed  Google Scholar 

  47. Ostir GV, Berges IM, Ottenbacher A, Ottenbacher KJ. Patterns of change in depression after stroke. J Am Geriatr Soc. 2011;59(2):314–20.

    PubMed  PubMed Central  Google Scholar 

  48. Tamara RZ, Žikić M . The functional status and quality of life of patients with post-stroke depression with a review on their cognitive and neurological status. Arch Epidemiol: 2018; AEPD:2;117.

  49. Nickel A, Thomalla G. Post-stroke depression: impact of lesion location and methodological limitations—a topical review. Front. Neurol. 2017;8:498.

    PubMed  PubMed Central  Google Scholar 

  50. Wei N, Yong W, Li X, Zhou Y, Deng M, Zhu H, et al. Post-stroke depression and lesion location: a systematic review. J. Neurol. 2015;262:81–90.

    PubMed  Google Scholar 

  51. Rajashekaran P, Pai K, Thunga R, Unnikrishnan B. Post-stroke depression and lesion location: a hospital based cross-sectional study. Indian J Psychiatry. 2013;55(4):343–8.

    PubMed  PubMed Central  Google Scholar 

  52. Metoki N, Sugawara N, Hagii J, Saito S, Shiroto H, Tomita T, et al. Relationship between the lesion location of acute ischemic stroke and early depressive symptoms in Japanese patients. Ann Gen Psychiatry .2016; 15:12.

Download references

Acknowledgements

Not applicable.

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Department of Neuropsychiatry, Faculty of Medicine, Assiut University Hospital, Assiut, Egypt

    Eman M. Khedr & Ahmed A. Abdelrahman

  2. Neuropsychiatric Department, Faculty of Medicine, Aswan University Hospital, Aswan, Egypt

    Eman M. Khedr

  3. Department of Neuropsychiatry, South Valley University, Qena University Hospital, Qena, Egypt

    Tarek Desoky, Ahmed Fathi Zaki & Ayman Gamea

Authors
  1. Eman M. Khedr
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ahmed A. Abdelrahman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tarek Desoky
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed Fathi Zaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ayman Gamea
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

EMK, TD, AF, and AG contributed to the study concept and design, acquisition of the data, drafting and revision of the report, statistical analyses, and interpretation of the data. AFZ, TD, and AG contributed to case recruitments, acquisition of the data, and statistical analyses. EMK, AFZ, and AG contributed to the editing of this report. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Eman M. Khedr.

Ethics declarations

Ethics approval and consent to participate

An informed consent was obtained from all the patients before participating in the study. The protocol was approved in January 2014 by the South Valley Medical School Ethical Review Board and all participants or relatives gave written informed consent before participation in the study. The confidentiality of the patients’ information was maintained during all the steps of the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khedr, E.M., Abdelrahman, A.A., Desoky, T. et al. Post-stroke depression: frequency, risk factors, and impact on quality of life among 103 stroke patients—hospital-based study. Egypt J Neurol Psychiatry Neurosurg 56, 66 (2020). https://doi.org/10.1186/s41983-020-00199-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s41983-020-00199-8

Keywords