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对 World Falls Guidelines 算法进行两项简单的修改,可提高其对老年人进行低、中、高跌倒风险分层的能力。

Two simple modifications to the World Falls Guidelines algorithm improves its ability to stratify older people into low, intermediate and high fall risk groups.

机构信息

Falls, Balance and Injury Research Centre, Neuroscience Research Australia, Sydney, NSW 2031, Australia.

School of Population Health, Faculty of Medicine and Health, University of New South Wales, Kensington, NSW 2052, Australia.

出版信息

Age Ageing. 2024 Oct 1;53(10). doi: 10.1093/ageing/afae192.

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.

摘要

背景

我们对一项队列研究进行了二次分析,以检验世界跌倒指南算法将老年人分层为大量跌倒风险组的能力,或者是否需要进行微小修改才能实现这一目标。

方法

693 名 70-90 岁的社区居住者(52.4%为女性)使用原始算法和修改后的算法(应用更广泛的计时起立行走测试,>10 秒的截断点[原为>15 秒])分为低、中、高跌倒风险组。比较三组的前瞻性跌倒率和身体及神经心理学表现。

结果

原始算法无法识别三个相当大的组,即只有 5 名参与者(0.7%)被归类为中等风险。修改后的算法将 349 名参与者(50.3%)归类为低风险,127 名参与者(18.3%)归类为中等风险,217 名参与者(31.3%)归类为高风险。相当大的中等风险组的身体和神经心理学特征与高风险组相似,但跌倒率与低风险组相似。高风险组的跌倒率明显高于低风险组[发病率比(IRR)=2.52,95%置信区间(CI)=1.99-3.20]和中风险组(IRR=2.19,95%CI=1.58-3.03)。

结论

修改后的算法将老年人分为三个相当大的跌倒风险组,包括一个中间组,这些人可能有在中到长期内过渡到高跌倒率的风险。这些简单的修改可能有助于更好地将老年人分诊到适当和量身定制的跌倒预防干预措施中。

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