Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, Yi-Lan, Taiwan.
Aging and Health Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan.
Sci Rep. 2021 Nov 30;11(1):23149. doi: 10.1038/s41598-021-02656-7.
The present study aimed to determine whether a recently proposed cerebral small vessel disease (CSVD) classification scheme could differentiate the 5-year all-cause mortality in middle-to-old aged asymptomatic CSVD. Stroke-free and non-demented participants recruited from the community-based I-Lan Longitudinal Aging Study underwent baseline brain magnetic resonance imaging (MRI) between 2011 and 2014 and were followed-up between 2018 and 2019. The study population was classified into control (non-CSVD) and CSVD type 1-4 groups based on MRI markers. We determined the association with mortality using Cox regression models, adjusting for the age, sex, and vascular risk factors. A total of 735 participants were included. During a mean follow-up of 5.7 years, 62 (8.4%) died. There were 335 CSVD type 1 (57.9 ± 5.9 years), 249 type 2 (65.6 ± 8.1 years), 52 type 3 (67.8 ± 9.2 years), and 38 type 4 (64.3 ± 9.0 years). Among the four CSVD types, CSVD type 4 individuals had significantly higher all-cause mortality (adjusted hazard ratio = 5.0, 95% confidence interval 1.6-15.3) compared to controls. This novel MRI-based CSVD classification scheme was able to identify individuals at risk of mortality at an asymptomatic, early stage of disease and might be applied for future community-based health research and policy.
本研究旨在确定最近提出的脑小血管疾病 (CSVD) 分类方案是否可以区分无症状 CSVD 的中老年人 5 年全因死亡率。2011 年至 2014 年期间,来自社区为基础的宜兰纵向老龄化研究的无卒中且无痴呆的参与者接受了基线脑部磁共振成像 (MRI),并于 2018 年至 2019 年进行了随访。根据 MRI 标志物,研究人群被分为对照组 (非 CSVD) 和 CSVD 类型 1-4 组。我们使用 Cox 回归模型确定与死亡率的相关性,调整年龄、性别和血管危险因素。共纳入 735 名参与者。在平均 5.7 年的随访期间,有 62 人 (8.4%) 死亡。CSVD 类型 1 有 335 例 (57.9 ± 5.9 岁),类型 2 有 249 例 (65.6 ± 8.1 岁),类型 3 有 52 例 (67.8 ± 9.2 岁),类型 4 有 38 例 (64.3 ± 9.0 岁)。在这四种 CSVD 类型中,CSVD 类型 4 个体的全因死亡率明显更高 (调整后的危险比 = 5.0,95%置信区间 1.6-15.3),与对照组相比。这种新的基于 MRI 的 CSVD 分类方案能够在无症状、疾病早期识别出有死亡风险的个体,可能适用于未来的社区为基础的健康研究和政策。