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世界跌倒预防与管理指南风险分层算法在爱尔兰老龄化纵向研究(TILDA)中预测跌倒的应用。

The use of the World Guidelines for Falls Prevention and Management's risk stratification algorithm in predicting falls in The Irish Longitudinal Study on Ageing (TILDA).

机构信息

Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

出版信息

Age Ageing. 2023 Jul 1;52(7). doi: 10.1093/ageing/afad129.

Abstract

BACKGROUND

the aim of this study was to retrospectively operationalise the World Guidelines for Falls Prevention and Management (WGFPM) falls risk stratification algorithm using data from The Irish Longitudinal Study on Ageing (TILDA). We described how easy the algorithm was to operationalise in TILDA and determined its utility in predicting falls in this population.

METHODS

participants aged ≥50 years were stratified as 'low risk', 'intermediate' or 'high risk' as per WGFPM stratification based on their Wave 1 TILDA assessments. Groups were compared for number of falls, number of people who experienced one or more falls and number of people who experienced an injury when falling between Wave 1 and Wave 2 (approximately 2 years).

RESULTS

5,882 participants were included in the study; 4,521, 42 and 1,309 were classified as low, intermediate and high risk, respectively, and 10 participants could not be categorised due to missing data. At Wave 2, 17.4%, 43.8% and 40.5% of low-, intermediate- and high-risk groups reported having fallen, and 7.1%, 18.8% and 18.7%, respectively, reported having sustained an injury from falling.

CONCLUSION

the implementation of the WGFPM risk assessment algorithm was feasible in TILDA and successfully differentiated those at greater risk of falling. The high number of participants classified in the low-risk group and lack of differences between the intermediate and high-risk groups may be related to the non-clinical nature of the TILDA sample, and further study in other samples is warranted.

摘要

背景

本研究旨在使用爱尔兰老龄化纵向研究(TILDA)的数据,回顾性地实施世界跌倒预防和管理指南(WGFPM)跌倒风险分层算法。我们描述了该算法在 TILDA 中实施的简便程度,并确定了其在预测该人群跌倒中的效用。

方法

根据 WGFPM 分层,对年龄≥50 岁的参与者进行分层,分为“低风险”、“中风险”或“高风险”,依据其在 TILDA 第 1 波的评估结果。比较各分组之间的跌倒次数、发生 1 次或多次跌倒的人数以及在第 1 波和第 2 波(大约 2 年)期间跌倒时受伤的人数。

结果

本研究纳入了 5882 名参与者;其中 4521 人、42 人和 1309 人分别被归类为低、中和高风险,10 人因数据缺失而无法归类。在第 2 波时,低、中、高风险组分别有 17.4%、43.8%和 40.5%的人报告跌倒,分别有 7.1%、18.8%和 18.7%的人报告因跌倒受伤。

结论

WGFPM 风险评估算法在 TILDA 中是可行的,并且成功地区分了那些跌倒风险较高的人群。大量参与者被归类为低风险组,而中风险组和高风险组之间缺乏差异,这可能与 TILDA 样本的非临床性质有关,需要在其他样本中进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/074c/10353759/33acd24df607/afad129f1.jpg

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