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首页> 外文期刊>Aging clinical and experimental research >Short Berg Balance Scale, BBS-9, as a predictor of fall risk among the aged: A prospective 12-month follow-up study
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Short Berg Balance Scale, BBS-9, as a predictor of fall risk among the aged: A prospective 12-month follow-up study

机译:短伯格平衡量表,BBS-9,作为老年人跌倒风险的预测指标:一项为期12个月的前瞻性随访研究

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Background and aims: The aim of this study was to assess the adequacy of the short, 9-item Berg Balance Scale (BBS-9) to predict fall risk among the community-dwelling aged. Methods: The subjects (n = 519) were derived from the participants in a multifactorial fall prevention intervention conducted in Pori, Finland. Receiver operating characteristic (ROC) analysis was used to determine the cut-off score for BBS-9 (range 0-36) to classify aged people with a fall risk during a 12-month follow-up. Logistic regression was used to analyse the relationship of potential con-founders with fall risk. The association between the cut-off score for BBS-9 and fall risk was tested using the Chisquare test. Results: In determining the cut-off score of BBS-9 to classify fall risk, the highest sensitivity (0.51) and specificity (0.57) (when both presumed to be above 0.50) sum score was within the limit range 32 scores or below. The area under curve (AUC) was significantly better in the model adjusted for significant confounders (vision and the number of regularly used drugs) (AUC = 0.64) than in the unadjusted model (AUC = 0.57) (p = 0.045). Among patients who scored 32 or below in BBS-9 the incidence of multiple falls was 20.0 %, whereas among those who scored 33-36 it was 15.7 %. Conclusions: BBS-9 with the cut-off score of 32/33 together with data on vision and the number of regularly used drugs predicted moderately the risk of falling among the community-dwelling aged.
机译:背景和目的:这项研究的目的是评估简短的9项Berg平衡量表(BBS-9)的适用性,以预测社区居住的老年人的跌倒风险。方法:对象(n = 519)来自在芬兰波里进行的多因素预防跌倒干预中的参与者。接收者工作特征(ROC)分析用于确定BBS-9(在0-36范围内)的临界值,以对12个月随访中有跌倒风险的老年人进行分类。使用逻辑回归分析潜在的混杂因素与跌倒风险的关系。使用Chisquare检验测试BBS-9的临界值与跌倒风险之间的关联。结果:在确定BBS-9的跌倒风险分类阈值时,最高敏感性(0.51)和特异性(0.57)(假设两者均高于0.50)的总和得分均在32分或以下的极限范围内。在针对重大混杂因素(视野和常规使用的药物数量)进行调整的模型(AUC = 0.64)中,曲线下面积(AUC)明显优于未经调整的模型(AUC = 0.57)(p = 0.045)。在BBS-9中得分为32或以下的患者中,多次摔倒的发生率为20.0%,而得分在33-36之间的患者为15.7%。结论:BBS-9的截止得分为32/33,以及视觉数据和经常使用的药物数量预测了社区居民中老年人跌倒的风险。

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