医学
置信区间
算法
比率
前瞻性队列研究
入射(几何)
人口学
队列
老年学
内科学
数学
几何学
社会学
作者
Cameron Hicks,Jasmine C. Menant,Kim Delbaere,Daina L. Sturnieks,Henry Brodaty,Perminder S. Sachdev,Stephen R. Lord
出处
期刊:Age and Ageing
[Oxford University Press]
日期:2024-10-01
卷期号:53 (10)
标识
DOI:10.1093/ageing/afae192
摘要
Abstract Background We conducted a secondary analysis of a cohort study to examine the World Falls Guidelines algorithm’s ability to stratify older people into sizable fall risk groups or whether minor modifications were necessary to achieve this. Methods Six hundred and ninety-three community-living people aged 70–90 years (52.4% women) were stratified into low, intermediate and high fall risk groups using the original algorithm and a modified algorithm applying broader Timed Up and Go test screening with a >10-s cut point (originally >15 s). Prospective fall rates and physical and neuropsychological performance among the three groups were compared. Results The original algorithm was not able to identify three sizable groups, i.e. only five participants (0.7%) were classified as intermediate risk. The modified algorithm classified 349 participants (50.3%) as low risk, 127 participants (18.3%) as intermediate risk and 217 participants (31.3%) as high risk. The sizable intermediate-risk group had physical and neuropsychological characteristics similar to the high-risk group, but a fall rate similar to the low-risk group. The high-risk group had a significantly higher rate of falls than both the low- [incidence rate ratio (IRR) = 2.52, 95% confidence interval (CI) = 1.99–3.20] and intermediate-risk groups (IRR = 2.19, 95% CI = 1.58–3.03). Conclusion A modified algorithm stratified older people into three sizable fall risk groups including an intermediate group who may be at risk of transitioning to high fall rates in the medium to long term. These simple modifications may assist in better triaging older people to appropriate and tailored fall prevention interventions.
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