痴呆
危险系数
医学
认知功能衰退
队列
队列研究
混淆
置信区间
比例危险模型
前瞻性队列研究
风险因素
儿科
老年学
精神科
内科学
疾病
作者
Joe Verghese,Cédric Annweiler,Emmeline Ayers,Nir Barzilai,Olivier Beauchet,David A. Bennett,Stephanie A. Bridenbaugh,Aron S. Buchman,Michele L. Callisaya,Richard Camicioli,Benjamin D. Capistrant,Somnath Chatterji,Anne-Marie De Cock,Luigi Ferrucci,Nir Giladi,Jack M. Guralnik,Jeffrey M. Hausdorff,Roee Holtzer,Ki Woong Kim,Paul Kowal
出处
期刊:Neurology
[Lippincott Williams & Wilkins]
日期:2014-07-17
卷期号:83 (8): 718-726
被引量:433
标识
DOI:10.1212/wnl.0000000000000717
摘要
Objectives:
Our objective is to report prevalence of motoric cognitive risk syndrome (MCR), a newly described predementia syndrome characterized by slow gait and cognitive complaints, in multiple countries, and its association with dementia risk. Methods:
Pooled MCR prevalence analysis of individual data from 26,802 adults without dementia and disability aged 60 years and older from 22 cohorts from 17 countries. We also examined risk of incident cognitive impairment (Mini-Mental State Examination decline ≥4 points) and dementia associated with MCR in 4,812 individuals without dementia with baseline Mini-Mental State Examination scores ≥25 from 4 prospective cohort studies using Cox models adjusted for potential confounders. Results:
At baseline, 2,808 of the 26,802 participants met MCR criteria. Pooled MCR prevalence was 9.7% (95% confidence interval [CI] 8.2%–11.2%). MCR prevalence was higher with older age but there were no sex differences. MCR predicted risk of developing incident cognitive impairment in the pooled sample (adjusted hazard ratio [aHR] 2.0, 95% CI 1.7–2.4); aHRs were 1.5 to 2.7 in the individual cohorts. MCR also predicted dementia in the pooled sample (aHR 1.9, 95% CI 1.5–2.3). The results persisted even after excluding participants with possible cognitive impairment, accounting for early dementia, and diagnostic overlap with other predementia syndromes. Conclusion:
MCR is common in older adults, and is a strong and early risk factor for cognitive decline. This clinical approach can be easily applied to identify high-risk seniors in a wide variety of settings.
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