Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
J Geriatr Phys Ther. 2023;46(2):103-109. doi: 10.1519/JPT.0000000000000362. Epub 2022 Aug 10.
The First-time Injurious Fall (FIF) screening tool was created to identify fall risk in community-living older men and women, who may be targets for primary preventive interventions. The FIF tool consists of 3 self-reported questions and 1 physical test (1-leg standing balance). The purpose of this study was to examine the predictive ability of the FIF tool and a modified FIF tool (in which 1-leg standing is replaced by self-reported balance) for first-time injurious falls.
A cohort of 1194 community-living people 60 years and older from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), Sweden, was followed longitudinally for 5 years. Data on injurious falls were collected from registered data and were defined as receipt of care after a fall. The predictive ability of the FIF tool and the m-FIF tool was explored using Harrell's C statistic, stratified by sex.
The injurious fall rate per 1000 person-years was 54.9 (95% CI: 47.22-63.78) for women and 36.3 (95% CI: 28.84-45.78) for men. The predictive ability for women and men according to Harrell's C statistic was 0.70 and 0.71 for the FIF tool and the m-FIF tool. The predictive ability was 0.70 and 0.69 for 1-leg standing, and 0.65 and 0.60 for self-reported balance problems.
The m-FIF tool presented similar predictive ability as the FIF tool regarding first-time injurious falls. This finding could extend the usefulness of the tool to other settings, such as to electronic health (eHealth). A quickly and easily administered screening tool can help physical therapists to identify people with a high risk of falling who may need to undergo a more comprehensive fall risk assessment.
首次受伤性跌倒（FIF）筛查工具旨在识别社区中生活的老年男女的跌倒风险，他们可能是初级预防干预的目标人群。FIF 工具包括 3 个自我报告问题和 1 个身体测试（单腿站立平衡）。本研究的目的是检验 FIF 工具和改良版 FIF 工具（将单腿站立改为自我报告平衡）对首次受伤性跌倒的预测能力。
来自瑞典 Kungsholmen 的全国老龄化和护理研究（SNAC-K）的 1194 名 60 岁及以上的社区居民队列进行了 5 年的纵向随访。受伤性跌倒的数据来自登记数据，定义为跌倒后接受护理。使用 Harrell 的 C 统计量分层分析男女两性，探讨 FIF 工具和 m-FIF 工具的预测能力。
女性每 1000 人年的受伤性跌倒率为 54.9（95%CI：47.22-63.78），男性为 36.3（95%CI：28.84-45.78）。根据 Harrell 的 C 统计量，女性和男性的预测能力分别为 FIF 工具和 m-FIF 工具的 0.70 和 0.71。1 腿站立的预测能力为 0.70 和 0.69，自我报告的平衡问题为 0.65 和 0.60。
改良版 FIF 工具在首次受伤性跌倒方面与 FIF 工具具有相似的预测能力。这一发现可以扩展工具的用途，例如在电子健康（eHealth）领域。一个快速简便的筛查工具可以帮助物理治疗师识别高跌倒风险的人群，他们可能需要进行更全面的跌倒风险评估。
