Yingyongyudha Anyamanee, Saengsirisuwan Vitoon, Panichaporn Wanvisa, Boonsinsukh Rumpa
1Division of Physical Therapy, Faculty of Health Science, Srinakharinwirot University, Nakhonnayok, Thailand. 2Department of Physiology, Faculty of Science, Mahidol University, Bangkok, Thailand.
J Geriatr Phys Ther. 2016 Apr-Jun;39(2):64-70. doi: 10.1519/JPT.0000000000000050.
Balance deficits a significant predictor of falls in older adults. The Balance Evaluation Systems Test (BESTest) and the Mini-Balance Evaluation Systems Test (Mini-BESTest) are tools that may predict the likelihood of a fall, but their capabilities and accuracies have not been adequately addressed. Therefore, this study aimed at examining the capabilities of the BESTest and Mini-BESTest for identifying older adult with history of falls and comparing the participants with history of falls identification accuracy of the BESTest, Mini-BESTest, Berg Balance Scale (BBS), and the Timed Up and Go Test (TUG) for identifying participants with a history of falls.
Two hundred healthy older adults with a mean age of 70 years were classified into participants with and without history of fall groups on the basis of their 12-month fall history. Their balance abilities were assessed using the BESTest, Mini-BESTest, BBS, and TUG. An analysis of the resulting receiver operating characteristic curves was performed to calculate the area under the curve (AUC), sensitivity, specificity, cutoff score, and posttest accuracy of each.
The Mini-BESTest showed the highest AUC (0.84) compared with the BESTest (0.74), BBS (0.69), and TUG (0.35), suggesting that the Mini-BESTest had the highest accuracy in identifying older adult with history of falls. At the cutoff score of 16 (out of 28), the Mini-BESTest demonstrated a posttest accuracy of 85% with a sensitivity of 85% and specificity of 75%. The Mini-BESTest had the highest posttest accuracy, with the others having results of 76% (BESTest), 60% (BBS), and 65% (TUG).
The Mini-BESTest is the most accurate tool for identifying older adult with history of falls compared with the BESTest, BBS, and TUG.
平衡能力缺陷是老年人跌倒的重要预测指标。平衡评估系统测试(BESTest)和简易平衡评估系统测试(Mini - BESTest)是可能预测跌倒可能性的工具,但其能力和准确性尚未得到充分探讨。因此,本研究旨在检验BESTest和Mini - BESTest识别有跌倒史老年人的能力,并比较BESTest、Mini - BESTest、伯格平衡量表(BBS)和计时起立行走测试(TUG)在识别有跌倒史参与者方面的准确性。
200名平均年龄为70岁的健康老年人根据其12个月的跌倒史被分为有跌倒史组和无跌倒史组。使用BESTest、Mini - BESTest、BBS和TUG评估他们的平衡能力。对所得的受试者工作特征曲线进行分析,以计算每条曲线下的面积(AUC)、敏感性、特异性、临界分数和测试后准确性。
与BESTest(0.74)、BBS(0.69)和TUG(0.35)相比,Mini - BESTest显示出最高的AUC(0.84),表明Mini - BESTest在识别有跌倒史的老年人方面具有最高的准确性。在28分制中临界分数为16分时,Mini - BESTest的测试后准确性为85%,敏感性为85%,特异性为75%。Mini - BESTest的测试后准确性最高,其他分别为76%(BESTest)、60%(BBS)和65%(TUG)。
与BESTest、BBS和TUG相比,Mini - BESTest是识别有跌倒史老年人最准确的工具。