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U-TEST:一种用于骨科患者肌少症诊断的简单决策支持工具:神户骨科人群肌少症筛查研究(SPSS-OK)。

U-TEST, a simple decision support tool for the diagnosis of sarcopenia in orthopaedic patients: the Screening for People Suffering Sarcopenia in Orthopedic cohort of Kobe study (SPSS-OK).

机构信息

Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto City, Kyoto, Japan.

Department of Sociology, Kansai University, Suita City, Osaka, Japan.

出版信息

Br J Nutr. 2021 Nov 14;126(9):1323-1330. doi: 10.1017/S0007114521000106. Epub 2021 Jan 14.

Abstract

We aimed to develop and validate a new simple decision support tool (U-TEST) for diagnosis of sarcopenia in orthopaedic patients. We created seventeen candidate original questions to detect sarcopenia in orthopaedic patients with sarcopenia through expert opinions and a semi-structured interview. To derive a decision support tool, a logistic regression model with backward elimination was applied to select variables from the seventeen questions, age and underweight (BMI < 18·5 kg/m2). Sarcopenia was defined by Asian Working Group for Sarcopenia 2019 criteria. After assigning a score to each selected variable, the sum of scores was calculated. We evaluated the diagnostic performance of the new tool using a logistic regression model. A bootstrap technique was used for internal validation. Among a total of 1334 orthopaedic patients, sixty-five (4·9 %) patients were diagnosed with sarcopenia. We succeeded in developing a 'U-TEST' with scores ranging from 0 to 11 consisting of values for BMI (Underweight), age (Elderly) and two original questions ('I can't stand up from a chair without supporting myself with my arms' (Strength) and 'I feel that my arms and legs are thinner than they were in the past' (Thin)). The AUC was 0·77 (95 % CI 0·71, 0·83). With the optimal cut-off set at 3 or greater based on Youden's index, the sensitivity and the specificity were 76·1 and 63·6 %, respectively. In orthopaedic patients, our U-TEST scoring with two questions and two simple clinical variables can help to screen for sarcopenia.

摘要

我们旨在开发和验证一种新的简单决策支持工具(U-TEST),用于诊断骨科患者的肌肉减少症。我们通过专家意见和半结构化访谈创建了十七个候选原始问题,以通过检测骨科患者的肌肉减少症来检测肌肉减少症。为了得出决策支持工具,应用向后消除的逻辑回归模型从十七个问题、年龄和体重不足(BMI<18.5kg/m2)中选择变量。肌肉减少症根据亚洲肌肉减少症工作组 2019 标准定义。为每个选定的变量分配分数后,计算分数总和。我们使用逻辑回归模型评估新工具的诊断性能。使用自举技术进行内部验证。在总共 1334 名骨科患者中,有 65 名(4.9%)患者被诊断为肌肉减少症。我们成功地开发了一个“U-TEST”,分数范围为 0 至 11,由 BMI(体重不足)、年龄(老年人)和两个原始问题(“我不能站在椅子上而不支撑我的手臂”(力量)和“我觉得我的手臂和腿比过去瘦了”(瘦))的值组成。AUC 为 0.77(95%CI 0.71,0.83)。根据 Youden 指数,将最优截断值设定为 3 或更高,敏感性和特异性分别为 76.1%和 63.6%。在骨科患者中,我们的 U-TEST 评分与两个问题和两个简单的临床变量相结合,可以帮助筛查肌肉减少症。

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