Accuracy of clinical-functional tools to identify risk of falls among community-dwelling older adults

Abstract Introduction: The identification of older adults who present greater chances of falling is the first step in the prevention of falls. Clinical instruments have been shown to be able to differentiate fallers from non-fallers, but their predictive validity remains controversial. Objective: To investigate the accuracy of the Short Physical Performance Battery (SPPB) and Quick Screen Clinical Fall Risk Assessment (QuickScreen) instruments to identify risk of falls in community-dwelling older adults. Method: This is a prospective methodological study with 81 older adults (≥ 60 years), assessed at baseline by SPPB and QuickScreen and monitored after one year to identify the occurrence of falls. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the ROC curve (AUC) were calculated. Results: 28.4% of the sample reported falls. QuickScreen presented 52.2% sensitivity, 74.1% specificity, 44.4% PPV, 79.6% NPV and 0.656 AUC. The AUC for SPPB was not significant (p = 0.087). Conclusion: QuickScreen presented poor accuracy when predicting falls and SPPB was unable to identify community-dwelling older adults at risk of falls. The QuickScreen instrument stood out for its high potential to identify true negatives.

摘要 引言：识别跌倒风险较高的老年人是跌倒预防的首要步骤。已有研究表明，临床评估工具可区分跌倒者与非跌倒者，但其预测效度仍存在争议。
研究目的：探讨简易体能状况量表（Short Physical Performance Battery, SPPB）与快速临床跌倒风险筛查量表（Quick Screen Clinical Fall Risk Assessment, QuickScreen）在识别社区居住老年人跌倒风险中的准确性。
研究方法：本研究为前瞻性方法学研究，纳入81名年龄≥60岁的老年人，于基线时采用SPPB与QuickScreen进行评估，并随访1年以记录跌倒发生情况。计算灵敏度、特异度、阳性预测值（positive predictive value, PPV）、阴性预测值（negative predictive value, NPV）以及受试者工作特征曲线（Receiver Operating Characteristic, ROC）下面积（area under the curve, AUC）。
研究结果：样本中有28.4%的老年人报告发生过跌倒。QuickScreen的灵敏度为52.2%、特异度74.1%、阳性预测值44.4%、阴性预测值79.6%，ROC曲线下面积为0.656。SPPB的ROC曲线下面积无统计学意义（p=0.087）。
研究结论：QuickScreen在预测跌倒时准确性较差，SPPB无法识别社区居住老年人的跌倒风险。QuickScreen量表在识别真阴性结果方面具有较高潜力。