Trajectories in physical performance and fall prediction in older adults: A longitudinal population-based study.
Trajectories in physical performance and fall prediction in older adults: A longitudinal population-based study.
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DOI：
10.1111/jgs.17995
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发表时间：
2022-12
影响因子：
6.3
通讯作者：
Burke, James F.
中科院分区：
文献类型：
--
作者：
Kerber, Kevin A.;Bi, Ran;Skolarus, Lesli E.;Burke, James F.
体能评估可以告知老年人的跌倒风险，但是，一次性评估的预测性有限。随着时间的推移，身体表现的轨迹还没有得到很好的表征，可能会改善跌倒预测。我们的目的是描述身体表现的轨迹，并确定跌倒预测是否使用性能轨迹得到改善。这是一个队列设计，使用的数据来自国家健康和老龄化趋势研究。通过短体能成套测验（SPPB）测量体能，评分范围为0（最差）至12（最佳）。使用潜在类建模和基于斜率的多级线性回归对SPPB的轨迹进行分类。我们使用考克斯比例风险模型，根据年度自我报告的至≥2次福尔斯的时间结局，评估在基线SPPB模型中添加SPPB轨迹和已建立的非基于体能的变量后的预测性。样本为5969名年龄≥65岁的社区居住医疗保险受益人。年度SPPB评价的中位数为4（IQR，3-7）。平均基线SPPB为9.2（SD，3.0）。潜在类模型定义的SPPB轨迹的范围内的两个到十九个类别。基于斜率的模型的平均斜率为-0.01 SPPB点/年（SD，0.14）。基线SPPB模型预测至≥2次福尔斯时间的区分度一般（Harrell's C，0.65），在添加非基于性能的预测因子后增加（Harrell's C，0.70）。使用最佳拟合的SPPB轨迹类别变量（Harrell's C，0.71），辨别力略有改善，但SPPB线性斜率没有改善。有和没有轨迹类别的校准是相似的。我们发现，从基线体能评估和已建立的非基于体能的信息中预测跌倒后，体能的轨迹并没有显著改善。这些结果不支持跌倒预测的纵向SPPB评估。
A physical performance evaluation can inform fall risk in older people, however, the predictiveness of a one‐time assessment is limited. The trajectory of physical performance over time has not been well characterized and might improve fall prediction. We aimed to characterize trajectories in physical performance and determine if fall prediction improves using trajectories of performance. This was a cohort design using data from the National Health and Aging Trends Study. Physical performance was measured by the short physical performance battery (SPPB) with scores ranging from 0 (worst) to 12 (best). The trajectory of SPPB was categorized using latent class modeling and slope‐based multilevel linear regression. We used Cox proportional hazards models with an outcome of time to ≥2 falls from annual self‐report to assess predictiveness after adding SPPB trajectories to models of baseline SPPB and established non‐physical‐performance‐based variables. The sample was 5969 community‐dwelling Medicare beneficiaries aged ≥65 years. The median number of annual SPPB evaluations was 4 (IQR, 3–7). Mean baseline SPPB was 9.2 (SD, 3.0). The latent class model defined SPPB trajectories over a range of two to nineteen categories. The mean slope from the slope‐based model was −0.01 SPPB points/year (SD, 0.14). Discrimination of the baseline SPPB model to predict time to ≥2 falls was fair (Harrell's C, 0.65) and increased after adding the non‐performance‐based predictors (Harrell's C, 0.70). Discrimination slightly improved with the SPPB trajectory category variable that had the best fit (Harrell's C, 0.71) but did not improve with the SPPB linear slope. Calibration with and without the trajectory categories was similar. We found that the trajectory of physical performance did not meaningfully improve upon fall prediction from a baseline physical performance assessment and established non‐performance‐based information. These results do not support longitudinal SPPB assessments for fall prediction.
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DOI：
10.1016/j.jamda.2019.04.014
发表时间：
2019-10-01
影响因子：
7.6
作者：
Ahmed, Tamer;French, Simon D.;Auais, Mohammad
通讯作者：
Auais, Mohammad
影响因子：
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作者：
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DOI：
10.1093/gerona/gly013
发表时间：
2019-02-01
影响因子：
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作者：
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通讯作者：
Markides, Kyriakos S.
影响因子：
4.8
作者：
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影响因子：
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作者：
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