Kaddumukasa Martin N, Kaddumukasa Mark, Katabira Elly, Sewankambo Nelson, Namujju Lillian D, Goldstein Larry B
Makerere University.
University of Kentucky.
Res Sq. 2023 Jan 16:rs.3.rs-2456615. doi: 10.21203/rs.3.rs-2456615/v1.
Background Little is known about the characteristics and determinants of post-stroke cognitive impairments in 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 From August 2019 to July 2020, patients were enrolled a minimum of 3-months post-stroke hospital admission. We collected data on their demographics, vascular risk factors and clinical factors using a questionnaire, clinical examination findings, and test results. 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. Discussion Further longitudinal, prospective studies are required to confirm these findings and identify strategies for reducing the risk of post-stroke cognitive impairment in this population.
在低收入和中等收入国家，对于中风后认知障碍的特征和决定因素知之甚少。本研究的目的是在一项对撒哈拉以南非洲乌干达穆拉戈医院连续收治的中风患者进行的横断面研究中，确定认知障碍的发生率、模式和风险因素。方法：2019年8月至2020年7月，对中风后至少住院3个月的患者进行入组。我们通过问卷调查、临床检查结果和检测结果收集了他们的人口统计学、血管危险因素和临床因素的数据。确定与认知障碍相关的独立预测变量。分别使用美国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、残疾和残障情况。使用蒙特利尔认知评估量表（MoCA）评估参与者的认知功能。采用逐步多元逻辑回归分析来确定与认知障碍独立相关的变量。结果：128例有可用数据的患者的MoCA总分平均为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）、低教育水平（OR 3.23，95% CI 1.25 - 8.33；p = 0.016）、功能残障（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。讨论：需要进一步进行纵向、前瞻性研究以证实这些发现，并确定降低该人群中风后认知障碍风险的策略。
