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优化住院脑卒中康复患者的跌倒风险预测:二次数据分析。

Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis.

机构信息

Department of Physical Therapy, University of Toronto, Toronto, ON, Canada.

Hennick Bridgepoint Hospital, Sinai Health, Toronto, ON, Canada.

出版信息

Physiother Theory Pract. 2023 Aug 3;39(8):1704-1715. doi: 10.1080/09593985.2022.2043498. Epub 2022 Mar 9.


DOI:10.1080/09593985.2022.2043498
PMID:35262449
Abstract

BACKGROUND: Identifying individuals at risk for falls during inpatient stroke rehabilitation can ensure timely implementation of falls prevention strategies to minimize the negative personal and health system consequences of falls. OBJECTIVES: To compare sociodemographic and clinical characteristics of fallers and non-fallers; and evaluate the ability of the Berg Balance Scale (BBS) and Morse Falls Scale (MFS) to predict falls in an inpatient stroke rehabilitation setting. METHODS: A longitudinal study involving a secondary analysis of health record data from 818 patients with stroke admitted to an urban, rehabilitation hospital was conducted. A fall was defined as having ≥1 fall during the hospital stay. Cut-points on the BBS and MFS, alone and in combination, that optimized sensitivity and specificity for predicting falls, were identified. RESULTS: Low admission BBS score and admission to a low-intensity rehabilitation program were associated with falling (p < .05). Optimal cut-points were 29 for the BBS (sensitivity: 82.4%; specificity: 57.4%) and 30 for the MFS (sensitivity: 73.2%; specificity: 31.4%) when used alone. Cut-points of 45 (BBS) and 30 (MFS) in combination optimized sensitivity (74.1%) and specificity (42.7%). CONCLUSIONS: A BBS cut-point of 29 alone appears superior to using the MFS alone or combined with the BBS to predict falls.

摘要

背景:在住院脑卒中康复期间识别有跌倒风险的个体可以确保及时实施跌倒预防策略,将跌倒对个人和医疗系统造成的负面影响降到最低。

目的:比较跌倒患者和非跌倒患者的社会人口学和临床特征;并评估 Berg 平衡量表(BBS)和 Morse 跌倒量表(MFS)在预测住院脑卒中康复环境中跌倒的能力。

方法:进行了一项纵向研究,对 818 名入住城市康复医院的脑卒中患者的健康记录数据进行了二次分析。定义跌倒为在住院期间发生≥1 次跌倒。确定了 BBS 和 MFS 单独和联合使用时,用于预测跌倒的最佳切点,以优化敏感性和特异性。

结果:入院时 BBS 评分较低和接受低强度康复计划与跌倒有关(p<.05)。单独使用时,BBS 的最佳切点为 29(敏感性:82.4%;特异性:57.4%),MFS 的最佳切点为 30(敏感性:73.2%;特异性:31.4%)。BBS 为 45(BBS)和 MFS 为 30(MFS)的切点联合优化了敏感性(74.1%)和特异性(42.7%)。

结论:单独使用 BBS 切点 29 似乎优于单独使用 MFS 或与 BBS 联合使用来预测跌倒。

相似文献

[1]
Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis.

Physiother Theory Pract. 2023-8-3

[2]
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Singapore Med J. 2015-5

[3]
Use of the Berg Balance Scale to predict independent gait after stroke: a study of an inpatient population in Japan.

PM R. 2015-4

[4]
Predicting the probability for fall incidence in stroke patients using the Berg Balance Scale.

J Int Med Res. 2009

[5]
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J Stroke Cerebrovasc Dis. 2016-7

[6]
The accuracy of individual Berg Balance Scale items compared with the total Berg score for classifying people with chronic stroke according to fall history.

J Neurol Phys Ther. 2009-9

[7]
An analysis of fall incidence rate and risk factors in an inpatient rehabilitation unit: A retrospective study.

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[8]
Combining the AM-PAC "6-Clicks" and the Morse Fall Scale to Predict Individuals at Risk for Falls in an Inpatient Rehabilitation Hospital.

Arch Phys Med Rehabil. 2021-12

[9]
Association Between Performance on an Interdisciplinary Stroke Assessment Battery and Falls in Patients With Acute Stroke in an Inpatient Rehabilitation Facility: A Retrospective Cohort Study.

Arch Phys Med Rehabil. 2019-6-13

[10]
The incidence and consequences of falls in stroke patients during inpatient rehabilitation: factors associated with high risk.

Arch Phys Med Rehabil. 2002-3

引用本文的文献

[1]
Advances in balance training to prevent falls in stroke patients: a scoping review.

Front Neurol. 2024-2-5

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