Development of a Practical Screening Tool to Predict Sarcopenia in Patients on Maintenance Hemodialysis

Abstract

Background Sarcopenia is a common complication in maintenance hemodialysis (MHD) and can increase patient hospitalization and mortality. No simple and reliable tools to identify sarcopenia exist. We aimed to develop a screening tool to predict MHD patients at high risk for sarcopenia. Material/Methods This cross-sectional study included 589 and 216 MHD patients for training and validation sets, respectively. We used diagnostic criteria developed by the Asian Working Group on Sarcopenia to screen for sarcopenia. The risk prediction model was established by univariate and multivariate logistic regression analyses. We used the area under the receiver operating characteristic curve (AUROC), calibration curve, Hosmer-Lemeshow test, and decision curve analysis (DCA) to evaluate the model’s discrimination ability, calibration ability, and clinical utility. Results The incidence of sarcopenia was 17.1% in the training set and 18.1% in the validation set. We constructed prediction models applying age, body mass index, calf circumference, and serum creatinine and plotted a nomogram. The training set model had an AUROC of 0.922, sensitivity of 85.1%, specificity of 85.9%, and chi-square value (Hosmer-Lemeshow test) of 5.603 ( P >0.05); the DCA diagram showed that when the threshold probability was 0 to 0.95, the model predicted a net benefit for sarcopenia in MHD patients. The validation set model had an AUROC of 0.913, sensitivity of 94.3%, specificity of 82.9%, and chi-square value (Hosmer-Lemeshow test) of 9.822 ( P >0.05). Conclusions The screening tool has good discrimination ability, calibration ability, and clinical utility. It could help to identify MHD patients at a high risk for sarcopenia.

WITHDRAWN: Development and external validation of a practical diagnostic support tool, ‘ABC 2-Screener’, to predict sarcopenia among patients on maintenance haemodialysis: A multicentre cross-sectional study

“…The ABC 2 -Screener showed useful discriminative and calibration performance in external validation, particularly for web-based programmes. The discriminative ability of the ABC 2 -Screener in external validation was excellent for both the point-scoring system and web-based programme (0.9149 and 0.9708, respectively) and equal to or superior to those of the aforementioned clinical prediction models (especially the web-based programme) (12)(13)(14)17). The external validation calibration of our tool showed a good fit across low to high predicted risk for the web-based programme while the intermediate predicted risk was underestimated for the point score system.…”

“…The MUAC measurements, which can be useful in predicting sarcopenia in the general population (31), are typically measured in the non-dominant arm. However, MUAC measurements in patients undergoing haemodialysis are generally performed on the side without vascular access which does not necessarily correspond to the dominant side; thus, MUAC measurements may differ between the dominant and non-dominant sides (13,32). Consequently, this may lead to misclassification.…”

“…Notably, clinical prediction rules should essentially be constructed with simple predictors that do not involve the measurements required to diagnose the target disease. Du et al’s nomogram for patients undergoing haemodialysis, consisting of four predictors (age, BMI, calf circumference (CC), and serum Cr), also demonstrated good calibration in external validation (13). However, the inclusion of CC as a predictive variable requires a tape measure that is not always available at dialysis facilities.…”

“…Several studies on clinical prediction rules have been conducted to screen for sarcopenia in patients undergoing dialysis. However, many of these are nomogram-based models (12)(13)(14) and may not be preferred in clinical practice because of the complexity at first sight and inaccuracies associated with translation to final outcomes (15,16). Additionally, in previously reported prediction rules, predictor variables included grip strength, a component of the criteria for diagnosing sarcopenia (14,17), and irisin and fat-free mass index, which are not measured in the usual course of care (17).…”

Prevalence and risk factors of sarcopenia in Chinese maintenance hemodialysis patients: a systematic review and meta-analysis

“…Furthermore, the risk factors for sarcopenia in Chinese MHD patients have been reported extensively, but some with controversial conclusions. 17 18 For example, Du W et al [17]. reported that albumin was associated with sarcopenia(OR 0.87, 95%CI 0.74 to 1.02).…”