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Background Muscle mass loss increases the risk of hyperglycaemia and sarcopenia in patients with type 2 diabetes mellitus (T2DM), and Chinese adults with T2DM are predominantly non-obese, who are more likely to be associated with muscle mass loss than the obese. Objective To establish an individualized Nomogram prediction model for the risk factors of muscle mass loss in non-obese patients with T2DM. Methods A retrospective study was conducted to select 905 non-obese patients with T2DM admitted to the Department of Endocrinology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from January 2018 to September 2023. The patients were divided into a training set (n=633) and a validation set (n=272) using simple random sampling at a ratio of 7∶3, and the general data and clinical indexes of the two groups of patients were collected and compared. Multivariate Logistic regression analysis was performed to determine risk factors for muscle mass loss in the training set and a Nomogram prediction model was constructed. The predictive value and clinical utility of the Nomogram prediction model were evaluated using receiver operating characteristic (ROC) curve, Hosmer-Lemeshow calibration curve, and decision curve analysis (DCA), respectively. Results The prevalence of muscle mass loss in non-obese patients with T2DM was 42.3% (383/905). Comparison of the clinical indicators of the patients in the training and validation sets showed no statistically significant differences (P>0.05). Multivariate Logistic regression analysis showed that age (OR=1.039, 95%CI=1.010-1.070, P=0.009), male (OR=3.425, 95%CI=2.133-5.499, P<0.001), BMI<23.5 kg/m2 (OR=19.678, 95%CI=11.319-34.210, P<0.001), elevated HbA1c (OR=1.196, 95%CI=1.081-1.323, P<0.001), increased visceral fat area (OR=1.021, 95%CI=1.010-1.032, P<0.001) were independent risk factors for muscle mass loss in non-obese patients with T2DM. The area under curve (AUC) of the ROC for the Nomogram prediction model to predict the risk of muscle mass loss occurring in patients in the training and validation sets was 0.825 (95%CI=0.793-0.856, P<0.001) and 0.806 (95%CI=0.753-0.859, P<0.001), respectively. The Hosmer-Lemeshow test showed that the model had a good fit (training set: χ2=11.822, P=0.159; validation set: χ2=8.189, P=0.415). Bootstrap method of plotting the calibration of the model showed that the calibration curves fitted well to the standard curves. The DCA curves showed that it was more beneficial to use the Nomogram prediction model to predict the incidence risk of muscle mass loss in patients with T2DM when the threshold probability of the patient was 0.06 to 0.94. Conclusion Age, male, BMI<23.5 kg/m2, elevated HbA1c, and increased visceral fat area are independent risk factors for muscle mass loss in non-obese patients with T2DM. The Nomogram prediction model established in this study can individually predict the risk of muscle mass loss in non-obese patients with T2DM, which facilitates the early identification of high-risk groups and the development of individualised interventions.