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帕金森病跌倒预测的准确性:6 个月和 12 个月的前瞻性分析。

Accuracy of fall prediction in Parkinson disease: six-month and 12-month prospective analyses.

机构信息

Program in Physical Therapy, Washington University in St. Louis School of Medicine, St. Louis, MO 63108, USA.

出版信息

Parkinsons Dis. 2012;2012:237673. doi: 10.1155/2012/237673. Epub 2011 Nov 30.

Abstract

Introduction. We analyzed the ability of four balance assessments to predict falls in people with Parkinson Disease (PD) prospectively over six and 12 months. Materials and Methods. The BESTest, Mini-BESTest, Functional Gait Assessment (FGA), and Berg Balance Scale (BBS) were administered to 80 participants with idiopathic PD at baseline. Falls were then tracked for 12 months. Ability of each test to predict falls at six and 12 months was assessed using ROC curves and likelihood ratios (LR). Results. Twenty-seven percent of the sample had fallen at six months, and 32% of the sample had fallen at 12 months. At six months, areas under the ROC curve (AUC) for the tests ranged from 0.8 (FGA) to 0.89 (BESTest) with LR+ of 3.4 (FGA) to 5.8 (BESTest). At 12 months, AUCs ranged from 0.68 (BESTest, BBS) to 0.77 (Mini-BESTest) with LR+ of 1.8 (BESTest) to 2.4 (BBS, FGA). Discussion. The various balance tests were effective in predicting falls at six months. All tests were relatively ineffective at 12 months. Conclusion. This pilot study suggests that people with PD should be assessed biannually for fall risk.

摘要

简介。我们分析了四项平衡评估在六个月和十二个月的前瞻性研究中预测帕金森病(PD)患者跌倒的能力。

材料和方法。在基线时,对 80 名特发性 PD 患者进行 BESTest、Mini-BESTest、功能性步态评估(FGA)和 Berg 平衡量表(BBS)测试。然后对 12 个月的跌倒情况进行跟踪。使用 ROC 曲线和似然比(LR)评估每个测试在六个月和十二个月时预测跌倒的能力。

结果。该样本中有 27%在六个月时跌倒,32%在十二个月时跌倒。在六个月时,测试的 ROC 曲线下面积(AUC)范围从 0.8(FGA)到 0.89(BESTest),LR+为 3.4(FGA)到 5.8(BESTest)。在十二个月时,AUC 范围从 0.68(BESTest、BBS)到 0.77(Mini-BESTest),LR+为 1.8(BESTest)到 2.4(BBS、FGA)。

讨论。各种平衡测试在六个月时有效预测跌倒。所有测试在十二个月时的效果相对较差。

结论。这项初步研究表明,PD 患者应每六个月评估一次跌倒风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23a2/3236452/575162d1fd5e/PD2012-237673.001.jpg

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