Strutz Nicole, Brodowski Hanna, Kiselev Joern, Heimann-Steinert Anika, Müller-Werdan Ursula
Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
Department of Physiotherapy, Pain and Exercise Research Lübeck, Institute of Health Sciences, University of Lübeck, Lübeck, Germany.
JMIR Aging. 2022 Aug 16;5(3):e36872. doi: 10.2196/36872.
Falls and the risk of falling in older people pose a high risk for losing independence. As the risk of falling progresses over time, it is often not adequately diagnosed due to the long intervals between contacts with health care professionals. This leads to the risk of falling being not properly detected until the first fall. App-based software able to screen fall risks of older adults and to monitor the progress and presence of fall risk factors could detect a developing fall risk at an early stage prior to the first fall. As smartphones become more common in the elderly population, this approach is easily available and feasible.
The aim of the study is to evaluate the app Lindera Mobility Analysis (LIN). The reference standards determined the risk of falling and validated functional assessments of mobility.
The LIN app was utilized in home- and community-dwelling older adults aged 65 years or more. The Berg Balance Scale (BBS), the Tinetti Test (TIN), and the Timed Up & Go Test (TUG) were used as reference standards. In addition to descriptive statistics, data correlation and the comparison of the mean difference of analog measures (reference standards) and digital measures were tested. Spearman rank correlation analysis was performed and Bland-Altman (B-A) plots drawn.
Data of 42 participants could be obtained (n=25, 59.5%, women). There was a significant correlation between the LIN app and the BBS (r=-0.587, P<.001), TUG (r=0.474, P=.002), and TIN (r=-0.464, P=.002). B-A plots showed only few data points outside the predefined limits of agreement (LOA) when combining functional tests and results of LIN.
The digital app LIN has the potential to detect the risk of falling in older people. Further steps in establishing the validity of the LIN app should include its clinical applicability.
German Clinical Trials Register DRKS00025352; https://tinyurl.com/65awrd6a.
跌倒及老年人的跌倒风险对其失去独立生活能力构成了高风险。随着跌倒风险随时间推移而增加，由于与医疗保健专业人员接触的间隔时间较长，其往往未得到充分诊断。这导致跌倒风险在首次跌倒之前未被正确检测到。基于应用程序的软件能够筛查老年人的跌倒风险并监测跌倒风险因素的进展和存在情况，可在首次跌倒之前的早期阶段检测到不断发展的跌倒风险。随着智能手机在老年人群中越来越普遍，这种方法易于获得且可行。
本研究旨在评估Lindera移动性分析（LIN）应用程序。参考标准确定了跌倒风险并验证了移动性功能评估。
LIN应用程序应用于年龄在65岁及以上的居家和社区居住的老年人。采用伯格平衡量表（BBS）、Tinetti测试（TIN）和计时起立行走测试（TUG）作为参考标准。除描述性统计外，还测试了数据相关性以及模拟测量（参考标准）和数字测量的平均差异比较。进行了Spearman等级相关分析并绘制了Bland-Altman（B-A）图。
可获得42名参与者的数据（n = 25，59.5%为女性）。LIN应用程序与BBS（r = -0.587，P <.001）、TUG（r = 0.474，P =.002）和TIN（r = -0.464，P =.002）之间存在显著相关性。当将功能测试与LIN结果相结合时，B-A图显示只有少数数据点超出了预先定义的一致性界限（LOA）。
数字应用程序LIN有潜力检测老年人的跌倒风险。建立LIN应用程序有效性的进一步步骤应包括其临床适用性。
德国临床试验注册中心DRKS00025352；https://tinyurl.com/65awrd6a 。
