Sit-to-Stand Video Analysis–Based App for Diagnosing Sarcopenia and Its Relationship With Health-Related Risk Factors and Frailty in Community-Dwelling Older Adults: Diagnostic Accuracy Study
Sit-to-Stand Video Analysis–Based App for Diagnosing Sarcopenia and Its Relationship With Health-Related Risk Factors and Frailty in Community-Dwelling Older Adults: Diagnostic Accuracy Study
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基于坐站视频分析的应用程序，用于诊断肌肉减少症及其与健康相关风险因素和社区老年人虚弱的关系：诊断准确性研究
DOI：
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发表时间：
2023
影响因子：
7.4
通讯作者：
J. J. Rodríguez
中科院分区：
文献类型：
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作者：
J. D. Ruiz;Alessio Montemurro;M. D. Martínez;J. J. Rodríguez
背景 可能的肌肉减少症是通过握力测试或 5 次坐站测试评估的肌肉力量减少来确定的，并通过双能 X 射线吸收测定法或生物电阻抗分析确定的肌肉量减少来确认。然而，这些参数并未在临床实践中实施，主要是由于缺乏设备和时间限制。如今，大多数智能手机设备中采用的技术创新（例如高速摄像机）提供了开发特定智能手机应用程序的机会，用于在简单的从坐到站的转换过程中测量与肌少症相关的运动参数。目的 我们的目的是创建和验证基于坐站视频分析的应用程序，用于诊断社区老年人的肌肉减少症，并分析其与健康相关风险因素和虚弱的构建有效性。方法 从老年社会中心招募了 686 名社区老年人（中位年龄：72 岁；59.2% [406/686] 女性）。指数测试是基于坐站视频分析的应用程序，使用肌肉力量和小腿围分别作为肌肉力量和肌肉数量的代表。参考标准是根据欧洲老年人肌肉减少症工作组-2（EWGSOP2）推荐的肌肉力量（握力或5次坐立测试结果）和肌肉量（四肢骨骼质量或骨骼肌指数）的不同组合得出的。计算受试者工作特征曲线的敏感性、特异性、阳性和阴性预测值以及曲线下面积 (AUC)，以确定应用程序的诊断准确性。使用逻辑回归评估构建有效性，以确定通过指数测试被分类为患有肌肉减少症的个体中与健康相关结果和虚弱（Fried 表型）相关的风险。结果 根据 EWGSOP2 指南提出的不同组合，肌肉减少症患病率从 2% 到 11% 不等。敏感性、特异性和 AUC 分别为 70%-83.3%、77%-94.9% 和 80.5%-87.1%，具体取决于所使用的诊断标准。同样，阳性和阴性预测值分别为 10.6%-43.6% 和 92.2%-99.4%。这些结果证明该应用程序可以可靠地排除这种疾病。此外，无论 EWGSOP2 提出的定义如何，那些根据指数测试被诊断为肌肉减少症的人与各自的同行相比，出现与健康相关的不良后果和虚弱的可能性更大。结论 该应用程序在检测功能良好的西班牙社区老年人的肌肉减少症方面表现出良好的诊断性能。与相应的同行相比，该应用程序诊断出的肌少症患者出现健康相关风险因素和虚弱的可能性更大。这些结果凸显了该应用程序在临床环境中的潜在用途。试验注册 ClinicalTrials.gov NCT05148351； https://clinicaltrials.gov/study/NCT05148351 国际注册报告标识符 (IRRID) RR2-10.3390/s22166010
Background Probable sarcopenia is determined by a reduction in muscle strength assessed with the handgrip strength test or 5 times sit-to-stand test, and it is confirmed with a reduction in muscle quantity determined by dual-energy X-ray absorptiometry or bioelectrical impedance analysis. However, these parameters are not implemented in clinical practice mainly due to a lack of equipment and time constraints. Nowadays, the technical innovations incorporated in most smartphone devices, such as high-speed video cameras, provide the opportunity to develop specific smartphone apps for measuring kinematic parameters related with sarcopenia during a simple sit-to-stand transition. Objective We aimed to create and validate a sit-to-stand video analysis–based app for diagnosing sarcopenia in community-dwelling older adults and to analyze its construct validity with health-related risk factors and frailty. Methods A total of 686 community-dwelling older adults (median age: 72 years; 59.2% [406/686] female) were recruited from elderly social centers. The index test was a sit-to-stand video analysis–based app using muscle power and calf circumference as proxies of muscle strength and muscle quantity, respectively. The reference standard was obtained by different combinations of muscle strength (handgrip strength or 5 times sit-to-stand test result) and muscle quantity (appendicular skeletal mass or skeletal muscle index) as recommended by the European Working Group on Sarcopenia in Older People-2 (EWGSOP2). Sensitivity, specificity, positive and negative predictive values, and area under the curve (AUC) of the receiver operating characteristic curve were calculated to determine the diagnostic accuracy of the app. Construct validity was evaluated using logistic regression to identify the risks associated with health-related outcomes and frailty (Fried phenotype) among those individuals who were classified as having sarcopenia by the index test. Results Sarcopenia prevalence varied from 2% to 11% according to the different combinations proposed by the EWGSOP2 guideline. Sensitivity, specificity, and AUC were 70%-83.3%, 77%-94.9%, and 80.5%-87.1%, respectively, depending on the diagnostic criteria used. Likewise, positive and negative predictive values were 10.6%-43.6% and 92.2%-99.4%, respectively. These results proved that the app was reliable to rule out the disease. Moreover, those individuals who were diagnosed with sarcopenia according to the index test showed more odds of having health-related adverse outcomes and frailty compared to their respective counterparts, regardless of the definition proposed by the EWGSOP2. Conclusions The app showed good diagnostic performance for detecting sarcopenia in well-functioning Spanish community-dwelling older adults. Individuals with sarcopenia diagnosed by the app showed more odds of having health-related risk factors and frailty compared to their respective counterparts. These results highlight the potential use of this app in clinical settings. Trial Registration ClinicalTrials.gov NCT05148351; https://clinicaltrials.gov/study/NCT05148351 International Registered Report Identifier (IRRID) RR2-10.3390/s22166010
DOI：
10.1093/gerona/56.3.m146
发表时间：
2001-03-01
影响因子：
5.1
作者：
Fried, LP;Tangen, CM;McBurnie, MA
通讯作者：
McBurnie, MA