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Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda

BACKGROUND: Little is known about the characteristics and determinants of post-stroke cognitive impairment in residents of low- and middle-income countries. The objective of this study was to determine the frequencies, patterns, and risk factors for cognitive impairment in a cross-sectional study of...

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Autores principales: Kaddumukasa, Martin N., Kaddumukasa, Mark, Katabira, Elly, Sewankambo, Nelson, Namujju, Lillian D., Goldstein, Larry B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127321/
https://www.ncbi.nlm.nih.gov/pubmed/37098461
http://dx.doi.org/10.1186/s12883-023-03212-8
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author Kaddumukasa, Martin N.
Kaddumukasa, Mark
Katabira, Elly
Sewankambo, Nelson
Namujju, Lillian D.
Goldstein, Larry B.
author_facet Kaddumukasa, Martin N.
Kaddumukasa, Mark
Katabira, Elly
Sewankambo, Nelson
Namujju, Lillian D.
Goldstein, Larry B.
author_sort Kaddumukasa, Martin N.
collection PubMed
description BACKGROUND: Little is known about the characteristics and determinants of post-stroke cognitive impairment in residents of low- and middle-income countries. The objective of this study was to determine the frequencies, patterns, and risk factors for cognitive impairment in a cross-sectional study of consecutive stroke patients cared for at Uganda’s Mulago Hospital, located in sub-Saharan Africa. METHODS: 131 patients were enrolled a minimum of 3-months after hospital admission for stroke. A questionnaire, clinical examination findings, and laboratory test results were used to collect demographic information and data on vascular risk factors and clinical characteristics. Independent predictor variables associated with cognitive impairment were ascertained. Stroke impairments, disability, and handicap were assessed using the National Institute of Health Stroke Scale (NIHSS), Barthel Index (BI), and modified Rankin scale (mRS), respectively. The Montreal Cognitive Assessment (MoCA) was used to assess participants’ cognitive function. Stepwise multiple logistic regression was used to identify variables independently associated with cognitive impairment. RESULTS: The overall mean MoCA score was 11.7-points (range 0.0–28.0-points) for 128 patients with available data of whom 66.4% were categorized as cognitively impaired (MoCA < 19-points). Increasing age (OR 1.04, 95% CI 1.00-1.07; p = 0.026), low level of education (OR 3.23, 95% CI 1.25–8.33; p = 0.016), functional handicap (mRS 3–5; OR 1.84, 95% CI 1.28–2.63; p < 0.001) and high LDL cholesterol (OR 2.74, 95% CI 1.14–6.56; p = 0.024) were independently associated with cognitive impairment. CONCLUSIONS: Our findings highlight the high burden and need for awareness of cognitive impairment in post stroke populations in the sub-Saharan region and serve to emphasize the importance of detailed cognitive assessment as part of routine clinical evaluation of patients who have had a stroke.
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spelling pubmed-101273212023-04-26 Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda Kaddumukasa, Martin N. Kaddumukasa, Mark Katabira, Elly Sewankambo, Nelson Namujju, Lillian D. Goldstein, Larry B. BMC Neurol Research BACKGROUND: Little is known about the characteristics and determinants of post-stroke cognitive impairment in residents of low- and middle-income countries. The objective of this study was to determine the frequencies, patterns, and risk factors for cognitive impairment in a cross-sectional study of consecutive stroke patients cared for at Uganda’s Mulago Hospital, located in sub-Saharan Africa. METHODS: 131 patients were enrolled a minimum of 3-months after hospital admission for stroke. A questionnaire, clinical examination findings, and laboratory test results were used to collect demographic information and data on vascular risk factors and clinical characteristics. Independent predictor variables associated with cognitive impairment were ascertained. Stroke impairments, disability, and handicap were assessed using the National Institute of Health Stroke Scale (NIHSS), Barthel Index (BI), and modified Rankin scale (mRS), respectively. The Montreal Cognitive Assessment (MoCA) was used to assess participants’ cognitive function. Stepwise multiple logistic regression was used to identify variables independently associated with cognitive impairment. RESULTS: The overall mean MoCA score was 11.7-points (range 0.0–28.0-points) for 128 patients with available data of whom 66.4% were categorized as cognitively impaired (MoCA < 19-points). Increasing age (OR 1.04, 95% CI 1.00-1.07; p = 0.026), low level of education (OR 3.23, 95% CI 1.25–8.33; p = 0.016), functional handicap (mRS 3–5; OR 1.84, 95% CI 1.28–2.63; p < 0.001) and high LDL cholesterol (OR 2.74, 95% CI 1.14–6.56; p = 0.024) were independently associated with cognitive impairment. CONCLUSIONS: Our findings highlight the high burden and need for awareness of cognitive impairment in post stroke populations in the sub-Saharan region and serve to emphasize the importance of detailed cognitive assessment as part of routine clinical evaluation of patients who have had a stroke. BioMed Central 2023-04-25 /pmc/articles/PMC10127321/ /pubmed/37098461 http://dx.doi.org/10.1186/s12883-023-03212-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Kaddumukasa, Martin N.
Kaddumukasa, Mark
Katabira, Elly
Sewankambo, Nelson
Namujju, Lillian D.
Goldstein, Larry B.
Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title_full Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title_fullStr Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title_full_unstemmed Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title_short Prevalence and predictors of post-stroke cognitive impairment among stroke survivors in Uganda
title_sort prevalence and predictors of post-stroke cognitive impairment among stroke survivors in uganda
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127321/
https://www.ncbi.nlm.nih.gov/pubmed/37098461
http://dx.doi.org/10.1186/s12883-023-03212-8
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