Department of Medicine, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda.
Department of Electrical and Computer Engineering, College of Engineering, Design, Art and Technology, Makerere University, Kampala, Uganda.
BMC Neurol. 2023 Apr 25;23(1):166. doi: 10.1186/s12883-023-03212-8.
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.
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.
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.
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.
在中低收入国家，人们对中风后认知障碍的特征和决定因素知之甚少。本研究的目的是确定乌干达马鲁戈医院中风患者的横断面研究中认知障碍的频率、模式和危险因素，该医院位于撒哈拉以南非洲地区。
131 名患者在中风后至少 3 个月入院时入组。使用问卷、临床检查结果和实验室检查结果收集人口统计学信息以及血管危险因素和临床特征的数据。确定与认知障碍相关的独立预测变量。使用国立卫生研究院中风量表（NIHSS）、巴氏指数（BI）和改良 Rankin 量表（mRS）评估中风损伤、残疾和功能障碍。使用蒙特利尔认知评估量表（MoCA）评估参与者的认知功能。采用逐步多因素逻辑回归分析确定与认知障碍独立相关的变量。
在 128 名可获得数据的患者中，总体平均 MoCA 评分为 11.7 分（范围 0.0-28.0 分），其中 66.4%被归类为认知障碍（MoCA<19 分）。年龄增长（OR 1.04，95%CI 1.00-1.07；p=0.026）、教育水平低（OR 3.23，95%CI 1.25-8.33；p=0.016）、功能障碍（mRS 3-5；OR 1.84，95%CI 1.28-2.63；p<0.001）和高 LDL 胆固醇（OR 2.74，95%CI 1.14-6.56；p=0.024）与认知障碍独立相关。
我们的研究结果突出了撒哈拉以南地区中风后人群认知障碍的高负担和认知障碍意识的必要性，并强调了详细认知评估作为中风患者常规临床评估的一部分的重要性。
