Dallaire-Théroux Caroline, Smith Colin, Duchesne Simon
CERVO Brain Research Center (CD-T, SD); Faculty of Medicine (CD-T), Université Laval; Department of Neurological Sciences (CD-T), Centre Hospitalier Universitaire de Québec, Canada; Academic Neuropathology (CS), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; and Department of Radiology and Nuclear Medicine (SD), Faculty of Medicine, Université Laval, Quebec City, Canada.
Neurol Clin Pract. 2024 Jun;14(3):e200271. doi: 10.1212/CPJ.0000000000200271. Epub 2024 Mar 21.
Sporadic cerebral small vessel disease (CSVD) is a class of important pathologic processes known to affect the aging brain and to contribute to cognitive impairment. We aimed to identify clinical risk factors associated with postmortem CSVD in middle-aged to older adults.
We developed and tested risk models for their predictive accuracy of a pathologic diagnosis of nonamyloid CSVD and cerebral amyloid angiopathy (CAA) in a retrospective sample of 160 autopsied cases from the Edinburgh Brain Bank. Individuals aged 40 years and older covering the spectrum of healthy aging and common forms of dementia (i.e., highly-prevalent etiologies such as Alzheimer disease (AD), vascular cognitive impairment (VCI), and mixed dementia) were included. We performed binomial logistic regression models using sample splitting and cross-validation methods. Demographics, lifestyle habits, traditional vascular risk factors, chronic medical conditions, , and cognitive status were assessed as potential predictors.
Forty percent of our sample had a clinical diagnosis of dementia (AD = 33, VCI = 26 and mixed = 5) while others were cognitively healthy (n = 96). The mean age at death was 73.8 (SD 14.1) years, and 40% were female. The presence of none-to-mild vs moderate-to-severe nonamyloid CSVD was predicted by our model with good accuracy (area under the curve [AUC] = 0.84, sensitivity [SEN] = 72%, specificity [SPE] = 95%), with the most significant clinical predictors being age, history of cerebrovascular events, and cognitive impairment. The presence of CAA pathology was also predicted with high accuracy (AUC = 0.86, SEN = 93%, SPE = 79%). Significant predictors included alcohol intake, history of cerebrovascular events, and cognitive impairment. In a subset of atypical dementias (n = 24), our models provided poor predictive performance for both nonamyloid CSVD (AUC = 0.50) and CAA (AUC = 0.43).
CSVD pathology can be predicted with high accuracy based on clinical factors in patients within the spectrum of AD, VCI, and normal aging. Whether this prediction can be enhanced by the addition of fluid and neuroimaging biomarkers warrants additional study. Improving our understanding of clinical determinants of vascular brain health may lead to novel strategies in the prevention and treatment of vascular etiologies contributing to cognitive decline.
This study provides Class II evidence that selected clinical factors accurately distinguish between middle-aged to older adults with and without cerebrovascular small vessel disease (amyloid and nonamyloid) pathology.
散发性脑小血管病（CSVD）是一类已知会影响衰老大脑并导致认知障碍的重要病理过程。我们旨在确定与中老年人群尸检时CSVD相关的临床风险因素。
我们开发并测试了风险模型，以评估其对来自爱丁堡脑库的160例尸检病例中，非淀粉样CSVD和脑淀粉样血管病（CAA）病理诊断的预测准确性。纳入了年龄在40岁及以上、涵盖健康衰老及常见痴呆形式（即阿尔茨海默病（AD）、血管性认知障碍（VCI）和混合性痴呆等高流行病因）的个体。我们使用样本拆分和交叉验证方法进行二项逻辑回归模型分析。将人口统计学、生活习惯、传统血管危险因素、慢性疾病以及认知状态作为潜在预测因素进行评估。
我们样本中的40%有痴呆的临床诊断（AD = 33例，VCI = 26例，混合性痴呆 = 5例），其余为认知健康者（n = 96）。平均死亡年龄为73.8（标准差14.1）岁，40%为女性。我们的模型对无至轻度与中度至重度非淀粉样CSVD的存在具有较高的预测准确性（曲线下面积[AUC] = 0.84，敏感性[SEN] = 72%，特异性[SPE] = 95%），最显著的临床预测因素为年龄、脑血管事件史和认知障碍。CAA病理的存在也具有较高的预测准确性（AUC = 0.86，SEN = 93%，SPE = 79%）。显著的预测因素包括酒精摄入量、脑血管事件史和认知障碍。在一组非典型痴呆患者（n = 24）中，我们的模型对非淀粉样CSVD（AUC = 0.50）和CAA（AUC = 0.43）的预测性能均较差。
基于AD、VCI和正常衰老范围内患者的临床因素，可高度准确地预测CSVD病理。添加液体和神经影像学生物标志物是否能增强这种预测有待进一步研究。增进我们对血管性脑健康临床决定因素的理解，可能会带来预防和治疗导致认知衰退的血管病因的新策略。
本研究提供了II类证据，表明所选临床因素能准确区分有无脑血管小血管病（淀粉样和非淀粉样）病理的中老年人群。
