Magnitude and predictors of post-stroke cognitive impairment among Ethiopian stroke survivors: A facility-based cross-sectional study

Abstract

Background: Stroke is emerging as a public health threat in sub-Saharan African countries including Ethiopia. Even though cognitive impairment is increasingly being recognized as a major cause of disability among stroke survivors there is a paucity of information on the magnitude of stroke-related cognitive dysfunction in Ethiopia. Thus, we assessed the magnitude and predictors of post-stroke cognitive impairment among Ethiopian stroke survivors.

Methods: A facility-based cross-sectional study was employed to assess the magnitude and predictor of post-stroke cognitive impairment among adult stroke survivors who came for follow-up at least 3 months after the last stoke episode from February to June 2021 in three outpatient neurology clinics in Addis Ababa, Ethiopia. We used the Montreal Cognitive Assessment Scale-Basic (MOCA-B), modified Rankin Scale (mRS), and Patient Health Questionnaire-9 (PHQ-9) to assess post-stroke cognition, functional recovery, and depression, respectively. Data were entered and analyzed using SPSS software version 25. A binary logistic regression model was employed to identify the predictors of post-stroke cognitive impairment. A p-value of 0.05 was considered statistically significant.

Results: Of the 79 stroke survivors approached, 67 were included. The mean (SD) age was 52.1 (12.7) years. Over half (59.7%) of the survivors were males and most (67.2%) were urban residents. The median stroke duration was 3 years ranging from 1 to 4 years.  Almost half (41.8%) of stroke survivors had cognitive impairment. Increased age (AOR=0.24, 95% CI=0.07,0.83), lower education (AOR=4.02, 95% CI=1.13,14.32), and poor function recovery (mRS ³3) (AOR=0.27, 95% CI=0.08-0.81) were predictors significantly associated with post-stroke cognitive impairment.

Conclusion: Nearly one in two stroke survivors had cognitive impairment. The major predictors associated with cognitive decline were age above 45 years, low literacy, and poor recovery in physical function. Although causality cannot be inferred, physical rehabilitation and better education are essential in building cognitive resilience among stroke survivors.

Introduction

Stroke remains one of the major causes of mortalities and most common causes of neurological disabilities among the elderlies worldwide. According to the 2019 Global Burden of Disease study, the age-standardized stroke related mortality and morbidity risks were 3.6 and 3.7 times higher in low-income groups than in high-income groups, respectively (1). Other than this, stroke survivors often suffering from profound cognitive dysfunction and neuropsychiatric changes with adverse outcomes on patients functionality and quality of life (2). Studies have reported stroke increases the risk of cognitive impairment 5 to 8 times (3) when compared with the general population including the lifetime risk of developing either stroke, dementia or both is approximated 1 in 3 persons worldwide (4). Post-stroke cognitive impairment (PSCI) is a multidomain disruption of cognitive function, including executive function, attention, concentration, language, memory, and visuospatial ability, associated with stroke (5). The severity of PSCI exists in a continuum from post-stroke mild cognitive impairment (PS-MCI) to post-stroke dementia (PSD).

Some studies have documented that the prevalence of PSCI to vary based on different settings, study designs, sample size, patient’s characteristics, diagnostic criteria, and assessment methods (6). In the western countries, the prevalence of cognitive impairment 3-months after stroke ranges from 22% in England (7) to 47.3% in France (8). Recent studies in Africa reported PSCI of 20% in Benin at 6 months after stroke (9) and 50% in Ghanaian stroke survivors after 2 years (10).

There ae several factors influencing PSCI. Those factors are ranging from demographic (age, gender, educational attainment), pre-stroke physical and cognitive status, index stroke features including hemorrhagic and recurrent strokes, post-stroke complications such as infection, delirium, depression and early seizures, and neuroimaging predictors such as cerebral small-vessel disease, cortical atrophy and medial temporal lobe atrophy. All these factors may all conspire to differentially influence the trajectory of cognitive impairment after stroke (11, 12).

The issue of stroke and other non-communicable diseases (NCDs) such as dementia are increasing due to the rapid epidemiological transition, lifestyle changes and population aging in most sub-Saharan Africa (SSA) countries (11). Despite the increment of the problem, there is a dearth of information regarding the epidemiology and burden of stroke related cognitive impairment. With this background information, we assessed the magnitude and predictors of post-stroke cognitive impairment in Ethiopian stroke survivors attending the outpatient clinics in three neurology referral clinics at the capital, Addis Ababa, Ethiopia to generate evidence that would contribute for the control and prevention strategies in the country.

Methods

Study participants

The main eligibility criteria for enrollment of patients were adult stroke survivors (18 years and above) who had a confirmed diagnosis of stroke and came for follow-up at least three months post-stroke and agreed to participate in the study. Patients with severe aphasia, known diagnosis of severe psychiatric illness or dementia, prior hearing and visual deficits and refused to participate were excluded.

Sample size and sample technique

The sample size was determined using G-power software. A power analysis for a one-tailed chi-test indicated that the minimum sample size to yield a statistical power of at least 0.95 with an alpha of 0.05 and a medium effect size of 0.4 (because we do not know the appropriate effect size) is 82. Patients fulfilling the above criteria were enrolled in order of arrival until the required sample size is attained.

Data collection tool and procedure

The important data were collected using a pretested structured interviewer-administered questionnaire containing socio-demographic, cardiovascular risk factors, and clinical features of stroke from patients and/or their caregivers. The cognitive test tools were prepared in English and forward translated into the local language (Amharic) and back translated to English to maintain its consistency. The Amharic version was pretested on 5% of the study participants to check the clarity of the questions and amended as appropriate.

Before data collection, five neurology residents who served as data collectors were trained for two days in the objective of the study and interviewing techniques to standardize their method of data collection. The collected data were checked every day for completeness and consistency by the investigators.

Cognitive assessment

Cognitive evaluation was done using the short form of informant questionnaire for Cognitive Decline in the Elderly (short IQCODE) to assess the pre-stroke cognitive status though in the final analysis it was dropped as two-third of the participants presented without an informant.

Post-stroke cognitive status (mild cognitive impairment (MCI) or dementia) was evaluated using the Montreal Cognitive Assessment – Basic (MOCA-B), which has been validated for screening MCI in low literacy (< 6 years of education) and uneducated individuals in several languages (13). The tool is a 30-point test and evaluates six cognitive domains (visual perception, executive functioning, language, attention, memory, and orientation). Literacy based MOCA-B cutoff classified patients with scores 17–22 for literate (14–19 for illiterate or under 6-year education) to have MCI, and ≤ 16 (≤ 13 for illiterate or under 6-year education) to have dementia, while scores of ≥ 23 for literate and ≥ 20 for illiterate and low education level were indicative of normal cognitive performance. (14).

Functional status was evaluated by the modified Rankin Scale (mRS), a six-point ordinal scale ranging from 0 (no symptoms) to 6 (death) and measures the degree of disability or dependence in everyday life, including instrumental and basic activities of daily living. It was categorized into good (mRS < 3) and poor (mRS ≥3) functional recovery.

Post-stroke depression was assessed using the Patient Health Questionnaire (PHQ-9) employed to screen for post stroke depression. The 9-item scale was scored as no depression = 0, mild depression = 1–9, moderated depression = 10–14 and severe depression = 15–27.

Results

Vascular risk factors and PSCI in stroke survivors

As shown in Table 2, hypertension (30%) was the major vascular risk factor identified followed by dyslipidemia (8.9%) and diabetes (7.4%). Infectious risks such as HIV and latent syphilis were identified in 8.7% and 4.4%, respectively. More than half (58.2%) of the participants had hospital admission and 17.9% had stroke related medical complications such as seizure and aspiration pneumonia. Although majority of the patients had first-ever stroke, 19.4% had a recurrence. Post stroke cognitive impairment was identified in 41.8% of stroke survivors and a third (30%) of them had MCI while the rest 12% had post stroke dementia.

Although statistically significance was not achieved, when patients were stratified by the disease duration the magnitude of cognitive dysfunction grow exponentially over the first five years and later it dropped. (Fig. 1)

The median duration [IQR] since index stroke was 36 [12–50] months which ranges from 4 to 132 months. Thirty-nine patients were admitted to the hospital after stroke episode and of those, 38.5% developed PSCI. As shown in Table 3 there were significant differences in the average age (SD) and average mRS score (SD) of patients who developed PSCI as compared to those without PSCI.

As depicted in Table 4, both in bivariate and multivariate logistic regression analysis, older age, low or lack of education, and poor functional recovery were significantly associated with PSCI. Stroke survivors with low or lack of education had 4 times increased risk for cognitive impairment when compared with educated patients (AOR = 4.02, 95% CI = 1.13,14.32). In addition, being middle and old aged (≥ 45 years) (AOR = 0.24, 95% CI = 0.07,0.83) and having poor recovery on motor functions (mRS ≥3) (AOR = 0.27, 95% CI = 0.08–0.81) were significantly associated with PSCI. However, the association between post-stroke cognitive dysfunction and gender, living arrangement, address and stroke subtypes did not reach the significance level.

Figure 2 showed the statistically significant inverse correlation between increasing age and lower MOCA-B mean score (r=-0.33, R² = 0.11, p = 0.006) (Fig. 2).

Discussion

In the present study, 42% of stoke survivors experienced some form of cognitive impairment which included PS-MCI in 30% and PSD in 12% with about in 3.4 years of average duration after the stroke incident. Our findings are comparable with prior studies conducted in high income countries which reported 32% in United Kingdom (15), 39% in Australia (16) and 47.3% in France (8) as well as in low and middle income countries such as Chile (39%) (17), Ghana (7.6%) (10) and Nigeria (48.3%) (18). On the other hand, compared with other HICs our findings are lower than Portugal (42 vs 55%) (19), Norway (42 vs 57%) (20) and South Korea (42 vs 69.8%) (21). Such differences might be attributed to the study settings and the sample used.

A community-based study by Qu Y et al showed the highest post stroke cognitive dysfunction at 80.9% where 49% had PSCI without dementia and 32% with PSD (22). This variation can be ascribed to the differences in the study design (institution-based), study area (urban setting), study participants (one third had stroke in the young), stroke duration (median of 3 years), and assessment method (MoCA-B) used in our study. Generally, the magnitude of PSCI reported in our study is similar to that in the existing literature.

Although stroke risk increases with age, the average age of stroke survivors in our cohort was 52 years and more than one-third had stroke at a younger age, which is defined as stroke occurrence before the age of 45 years. This result is in agreement with our prior study in the same setting (23). However, most other regional and global studies reported a relatively higher age for stroke related cognitive impairment (9, 10, 18, 20). This might be explained by the Ethiopia population demography where more than two-third of the population is young. which is predominantly male, and males often developed stroke at earlier age as compared to females. Similar to other African studies (10, 18), majority (60%) of our study participants were males. This could be attributed to the reality that in low-income countries such as Ethiopia males are the bread winners and financial decision makers of the house and this gives them the upper hand to seek better health services as compared to the females.

Several sociodemographic and clinical variables contribute to the cognitive outcome of stroke survivors. Among these, increasing in age was documented as the major predictor of PSCI in prior studies (2, 12, 18). Similarly to the aforementioned studies, we have observe a significant association between stroke onset at the age of 45 years and above and PSCI though our cohort is relatively younger. Likewise, a Ghanaian study identified that the risk of PSCI increased by 44% for every 10-year increase in age and the authors attribute this to possible synergistic interaction between the vascular insult and neurodegenerative process which ends up in cognitive dysfunction (10). In the present study almost half of the participants had little or no education and this was independently associated with PSCI with 4 times higher risk as compared to the literate group. A case-control study from Nigeria (18) reported that lower education was associated with 5 times increased risk of PSCI. To the contrary, better education increases the tenacity of brain function by improving cognitive reserve and this serves as a surrogate marker for cognitive reserve.

It is known that functional recovery is a proxy marker for stroke severity and clinical deficit, stroke location and vascular burden, and acute stroke care and rehabilitation (10, 12). Interestingly, we found a significant association between poor function recovery and PSCI. A meta-analysis of randomized controlled trials (24) revealed that a structured physical activity and neurorehabilitation training enhances cognitive performance after stroke as early as in 12 weeks. Therefore, one way to address the growing burden of stroke on cognitive and physical outcomes of patients is by incorporating a comprehensive and multimodal rehabilitation interventions at an early stage of stroke.

Strength and limitations of the study

Firstly, this study is the first of its kind to assess the magnitude of cognitive impairment in a sample of stroke survivors from Ethiopia. Secondly, we had attempted to show the association between cognitive dysfunction and demographic, clinical and stroke related factors. Nevertheless, the study had some limitations that include use of small sample size, the nature of the design employed and the study settings which were limited to three urban neurology centers which might have over represented the severe cases and therefore needs to be interpreted cautiously. The pre-stroke cognitive evaluation by short IQCODE was not considered in the analysis due to incomplete data.

Conclusion

Our study found a relatively higher magnitude of cognitive dysfunction among males than female stroke survivors in Ethiopia. The major predictors identified were age 45 years and above, low educational attainment and poor recovery of physical function. Although causality cannot be inferred, physical rehabilitation and better education might play a role in building cognitive resilience among stroke survivors.

Abbreviations

ETB: Ethiopian Birr; IQCODE: informant questionnaire for Cognitive Decline in the Elderly; LGH: Lancet general hospital; MCI: Mild cognitive impairment, MOCA-B: Montreal cognitive assessment-Basic; mRS: modified Rankin scale; PHQ-9: Patient health questionnaire-9; PSCI: Post-stroke cognitive impairment, PSD: Post-stroke dementia; TASH: Tikur Anbessa Specialized hospital: USD: United States dollar; YSC: Yehuleshet specialty clinic

Declarations

Ethics approval and consent to participate: The study protocol received ethical approval from the Institutional Ethics Review Board (IRB) of the College of Health Sciences, Addis Ababa University (Protocol no. 099/19/Neuro). A written informed consent was obtained from each participant (or their family caregivers or legal guardian in the case of illiterate or severely disabled subjects) before commencing with the interview. The study was performed in accordance with the Declaration of Helsinki.

Consent for publication: Not applicable

Availability of data and materials: The datasets supporting the conclusions of this article are included within the article and they are also available from the corresponding author upon reasonable request.

Competing interests: The authors declare they have no actual or potential competing financial interests.

Funding: This research project was financially supported by the Medical Education Partnership Initiative (MEPI) – Ethiopia under the NIH/Fogarty International Center (D43 TW010143)

Author’s contributions: YZZ contribute to study planning, designing, data acquisition, analysis, interpretation, and manuscript preparation. AA and SKS contribute to data interpretation, review, manuscript writeup and critique. All authors read and approved the final manuscript. 

Acknowledgements: We are thankful to the Department of Neurology faculties and residents and to Sr. Wubit Bekele, Head nurse of the Neurology clinic, for their unreserved supportin the study. We remain incredibly grateful for Prof. Jemal Haider thorough review and feedback on the manuscript. Finally, we would like to thank all participants and caregivers who took part in this study.

Author’s information

Yared Z. Zewde, MD is an Assistant Professor of Neurology at the Department of Neurology, CHS-AAU, Addis Ababa, Ethiopia. He is also a Global Atlantic fellow for Equity in Brain Health at the Global Brain Health Institute at the University of California, San Francisco (UCSF), USA with active engagement in dementia and cognitive neuroscience researches with particular interest in vascular risk factors and neurodegenerative dementia.

Atalay Alem, MD, PhD, is a Professor at the Department of Psychiatry, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia with an extensive experience in mental health research in Ethiopia.

Susanne K. Seeger, MD, is a Clinical Professor at the department of Neurology, University of Wisconsin, School of Medicine and Public Health, Wisconsin, USA with active engagement in cognition, pain, and vascular neurology.

References

1. Feigin VL, Stark BA, Johnson CO, Roth GA, Bisignano C, Abady GG, et al. Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021 Oct;20(10):795–820.
2. Pendlebury ST. Stroke-related dementia: Rates, risk factors and implications for future research. Maturitas. 2009 Nov;64(3):165–71.
3. Merino JG. Dementia after stroke: high incidence and intriguing associations. Stroke. 2002 Sep;33(9):2261–2.
4. Seshadri S, Beiser A, Kelly-Hayes M, Kase CS, Au R, Kannel WB, et al. The Lifetime Risk of Stroke: Estimates From the Framingham Study. Stroke. 2006 Feb;37(2):345–50.
5. Gorelick PB, Scuteri A, Black SE, DeCarli C, Greenberg SM, Iadecola C et al. Vascular Contributions to Cognitive Impairment and Dementia: A Statement for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke. 2011 Sep;42(9):2672–713.
6. Sun J-H, Tan L, Yu J-T. Post-stroke cognitive impairment: epidemiology, mechanisms and management. Ann Transl Med. 2014 Aug;2(8):80.
7. Douiri A, Rudd AG, Wolfe CDA. Prevalence of Poststroke Cognitive Impairment: South London Stroke Register 1995–2010. Stroke. 2013 Jan;44(1):138–45.
8. Jacquin A, Binquet C, Rouaud O, Graule-Petot A, Daubail B, Osseby G-V, et al. Post-Stroke Cognitive Impairment: High Prevalence and Determining Factors in a Cohort of Mild Stroke. J Alzheimers Dis. 2014 May;19(4):1029–38.
9. Gnonlonfoun DD, Ossou-Nguiet PM, Diallo LL, Adjien C, Avlessi I, Goudjinou G, et al. Post-Stroke Cognitive Disorders and Associated Factors in French Speaking West Africa, Benin Case. Neurosci Med. 2014;05(01):32–41.
10. Sarfo FS, Akassi J, Adamu S, Obese V, Ovbiagele B. Burden and Predictors of Poststroke Cognitive Impairment in a Sample of Ghanaian Stroke Survivors. J Stroke Cerebrovasc Dis. 2017 Nov;26(11):2553–62.
11. Pendlebury ST, Rothwell PM. Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: a systematic review and meta-analysis. Lancet Neurol. 2009 Nov;8(11):1006–18.
12. Leys D, Hénon H, Mackowiak-Cordoliani M-A, Pasquier F. Poststroke dementia. Lancet Neurol. 2005 Nov;4(11):752–9.
13. Julayanont P, Tangwongchai S, Hemrungrojn S, Tunvirachaisakul C, Phanthumchinda K, Hongsawat J, et al. The Montreal Cognitive Assessment-Basic: A Screening Tool for Mild Cognitive Impairment in Illiterate and Low-Educated Elderly Adults. J Am Geriatr Soc. 2015 Dec;63(12):2550–4.
14. Saleh AA, Alkholy RSAEHA, Khalaf OO, Sabry NA, Amer H, El-Jaafary S et al. Validation of Montreal Cognitive Assessment-Basic in a sample of elderly Egyptians with neurocognitive disorders. Aging Ment Health 2019 May 4;23(5):551–7.
15. Ballard C, Stephens S, McLAREN A, Wesnes K, Kenny RA, Burton E, et al. Neuropsychological Deficits in Older Stroke Patients. Ann N Y Acad Sci. 2002 Nov;977(1):179–82.
16. Sachdev PS, Brodaty H, Valenzuela MJ, Lorentz L, Looi JCL, Wen W, et al. The neuropsychological profile of vascular cognitive impairment in stroke and TIA patients. Neurology. 2004 Mar;23(6):912–9.
17. Delgado C, Donoso A, Orellana P, Vásquez C, Díaz V, Behrens MI. Frequency and Determinants of Poststroke Cognitive Impairment at Three and Twelve Months in Chile. Dement Geriatr Cogn Disord. 2010;29(5):397–405.
18. Akinyemi RO, Allan L, Owolabi MO, Akinyemi JO, Ogbole G, Ajani A, et al. Profile and determinants of vascular cognitive impairment in African stroke survivors: The CogFAST Nigeria Study. J Neurol Sci. 2014 Nov;346(1–2):241–9.
19. Madureira S, Guerreiro M, Ferro JM. Dementia and cognitive impairment three months after stroke. Eur J Neurol. 2001 Nov;14(6):621–7.
20. Ihle-Hansen H, Thommessen B, Wyller TB, Engedal K, Øksengård AR, Stenset V, et al. Incidence and subtypes of MCI and dementia 1 year after first-ever stroke in patients without pre-existing cognitive impairment. Dement Geriatr Cogn Disord. 2011;32(6):401–7.
21. Yu K-H, Cho S-J, Oh MS, Jung S, Lee J-H, Shin J-H, et al. Cognitive Impairment Evaluated With Vascular Cognitive Impairment Harmonization Standards in a Multicenter Prospective Stroke Cohort in Korea. Stroke. 2013 Mar;44(3):786–8.
22. Qu Y, Zhuo L, Li N, Hu Y, Chen W, Zhou Y et al. Prevalence of Post-Stroke Cognitive Impairment in China: A Community-Based, Cross-Sectional Study. Stewart R, editor. PLOS ONE. 2015 Apr 13;10(4):e0122864.
23. Zewde YZ, Mengesha AT, Gebreyes YF, Naess H. The frequency and impact of admission hyperglycemia on short term outcome of acute stroke patients admitted to Tikur Anbessa Specialized hospital, Addis Ababa, Ethiopia: a cross-sectional study. BMC Neurol. 2019 Dec;19(1):342.
24. Oberlin LE, Waiwood AM, Cumming TB, Marsland AL, Bernhardt J, Erickson KI. Effects of Physical Activity on Poststroke Cognitive Function: A Meta-Analysis of Randomized Controlled Trials. Stroke. 2017 Nov;48(11):3093–100.