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.
Keywords: Diagnostic performance; Osteoarthritis; Sarcopenia; Spinal stenosis.