尼日利亚博尔诺州迈杜古里大学教学医院（UMTH）急性缺血性中风患者的神经影像学检查结果及其预后价值

Neuroimaging Findings and Their Prognostic Value in Acute Ischaemic Stroke Patients at University of Maiduguri Teaching Hospital (UMTH), Borno State, Nigeria.

作者信息

Musa Iko, Joseph Musa, Musa Zakka, Kehinde Vinah Vivian, Tunwagun David Adesoye, Igweike Rita Chineze, Kawai Cynthia Udan, Yaga Jeremiah Maina, Ja'afar Ibrahim Khalil, Olokpo Mercy Akwum, Paul Grace Manmak, Chukwu Ifeoma Lauretta, Kanhu Patience Ungut, Amanum Innocent Onyekachi, Yakub Yusuf, Onyemaechi Mogbolu Wisdom

机构信息

Department of Community Medicine, University of Jos, Jos, Plateau State.

Department of Internal Medicine, Neurology Unit, University of Maiduguri Teaching Hospital, Maiduguri, Borno State.

出版信息

Niger Med J. 2025 Jun 16;66(2):551-563. doi: 10.71480/nmj.v66i2.681. eCollection 2025 Mar-Apr.

DOI:10.71480/nmj.v66i2.681

PMID:40703905

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12280294/

Abstract

BACKGROUND

Accurate prediction of stroke outcomes in resource-limited settings remains challenging. This study assessed the utility of neuroimaging findings in predicting mortality among acute ischaemic stroke patients at the University of Maiduguri Teaching Hospital, Nigeria.

METHODOLOGY

This prospective study enrolled 171 consecutive adults with acute ischaemic stroke between January and December 2023. All patients underwent non-contrast brain CT scanning, with infarct volume calculated using standardized measurements. The primary outcome was 30-day mortality. Multivariate logistic regression analysis identified independent predictors of mortality, which were used to develop a risk stratification system.

RESULTS

Large infarct volume (>100,000 mm) emerged as the strongest independent predictor of mortality (aOR 6.82, 95% CI 2.0522.68, p=0.002), followed by multiple territory involvement (aOR 3.42, 95% CI 1.43-8.17, p=0.006). The developed risk score demonstrated good discriminative ability (AUC 0.775, 95% CI 0.689-0.860) and stratified patients into three risk categories with mortality rates of 8.2% (low), 11.8% (intermediate), and 42.0% (high) (p<0.001).

CONCLUSION

Specific neuroimaging parameters can effectively predict early mortality in acute ischaemic stroke. The developed risk stratification tool could improve patient care in resource-limited settings.

摘要

背景

在资源有限的环境中准确预测中风结局仍然具有挑战性。本研究评估了神经影像学检查结果在预测尼日利亚迈杜古里大学教学医院急性缺血性中风患者死亡率方面的效用。

方法

这项前瞻性研究纳入了2023年1月至12月期间连续收治的171例急性缺血性中风成年患者。所有患者均接受了非增强脑CT扫描，并使用标准化测量方法计算梗死体积。主要结局是30天死亡率。多因素逻辑回归分析确定了死亡率的独立预测因素，并用于建立风险分层系统。

结果

大面积梗死体积（>100,000立方毫米）是死亡率最强的独立预测因素（调整后比值比6.82，95%置信区间2.05-22.68，p=0.002），其次是多区域受累（调整后比值比3.42，95%置信区间1.43-8.17，p=0.006）。所建立的风险评分显示出良好的鉴别能力（曲线下面积0.775，95%置信区间0.689-0.860），并将患者分为三个风险类别，死亡率分别为8.2%（低）、11.8%（中）和42.0%（高）（p<0.001）。