Supplementary Material for: A Prediction Model for Falls in Community-Dwelling Older Adults in Podiatry Practices

Introduction: Falls are a worldwide health problem among community-dwelling older adults. Emerging evidence suggests that foot problems increase the risk of falling, so the podiatrist may be crucial in detecting foot-related fall risk. However, there is no screening tool available which can be used in podiatry practice. The predictive value of existing tools is limited, and the implementation is poor. The development of risk models for specific clinical populations might increase the prediction accuracy and implementation. Therefore, the aim of this study was to develop and internally validate an easily applicable clinical prediction model (CPM) that can be used in podiatry practice to predict falls in community-dwelling older adults with foot (-related) problems. Methods: This was a prospective study including community-dwelling older adults (≥65 years) visiting podiatry practices. General fall-risk variables, and foot-related and function-related variables were considered as predictors for the occurrence of falls during the 12-month follow-up. Logistic regression analysis was used for model building, and internal validation was done by bootstrap resampling. Results: 407 participants were analyzed; the event rate was 33.4%. The final model included fall history in the previous year, unsteady while standing and walking, plantarflexor strength of the lesser toes, and gait speed. The area under the receiver operating characteristic curve was 0.71 (95% CI: 0.66–0.76) in the sample and estimated as 0.65 after shrinkage. Conclusion: A CPM based on fall history in the previous year, feeling unsteady while standing and walking, decreased plantarflexor strength of the lesser toes, and reduced gait speed has acceptable accuracy to predict falls in our sample of podiatry community-dwelling older adults and is easily applicable in this setting. The accuracy of the model in clinical practice should be demonstrated through external validation of the model in a next study.

引言：跌倒是全球社区居住的老年人普遍面临的健康问题。新近证据表明，足部问题会提高跌倒的风险，因此足病医生在检测与足部相关的跌倒风险中可能扮演关键角色。然而，目前尚无适用于足病实践的筛查工具。现有工具的预测价值有限，其应用效果不佳。针对特定临床人群的风险模型的开发可能提高预测准确性和实施效果。因此，本研究旨在开发并内部验证一种易于应用的临床预测模型（CPM），以便在足病实践中预测社区居住的老年人因足部（相关）问题而发生的跌倒。方法：这是一项前瞻性研究，纳入了访问足病实践的社区居住的老年人（≥65岁）。将一般跌倒风险变量、足部相关变量和功能相关变量作为预测因素，考虑其在12个月随访期间跌倒的发生。使用逻辑回归分析构建模型，并通过bootstrap重采样进行内部验证。结果：分析了407名参与者；事件发生率为33.4%。最终模型包括过去一年的跌倒史、站立和行走时的不稳感、小趾的足底屈肌力量以及步速。在样本中，接收者操作特征曲线下面积为0.71（95% CI：0.66–0.76），在缩减后估计为0.65。结论：基于过去一年的跌倒史、站立和行走时的不稳感、小趾足底屈肌力量下降和步速降低的临床预测模型（CPM）在我们的足病社区居住老年人样本中预测跌倒的准确性可接受，且易于在此环境中应用。该模型在临床实践中的准确性应通过在下一项研究中对模型进行外部验证来证明。