Construction and validation of a nomogram for predicting diabetes remission at 3 months after bariatric surgery in patients with obesity combined with type 2 diabetes mellitus

AIM: Bariatric metabolic surgery (BMS) is a proven treatment option for patients with both obesity and type 2 diabetes mellitus (T2DM). However, there is a lack of comprehensive reporting on the short-term remission rates of diabetes, and the existing data are inadequate. Hence, this study aimed to investigate the factors that may contribute to diabetes remission (DR) in patients with obesity and T2DM, 3 months after undergoing BMS. Furthermore, our objective was to develop a risk-predicting model using a nomogram. METHODS: In total, 389 patients with obesity and T2DM, who had complete preoperative information and underwent either laparoscopic sleeve gastrectomy or laparoscopic gastric bypass surgery between January 2014 and May 2023, were screened in the Chinese Obesity and Metabolic Surgery Database. The patients were randomly divided into a training set (n = 272) and a validation set (n = 117) in a 7:3 ratio. Potential factors for DR were analysed through univariate and multivariate logistic regression analyses and then modelled using a nomogram. The model's performance was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Calibration plots were used to assess prediction accuracy and decision curve analyses were conducted to evaluate the clinical usefulness of the model. RESULTS: Glycated haemoglobin, triglycerides, duration of diabetes, insulin requirement and hypercholesterolaemia were identified as independent factors influencing DR. We have incorporated these five indicators into a nomogram, which has shown good efficacy in both the training cohort (AUC = 0.930) and validation cohort (AUC = 0.838). The calibration plots indicated that the model fits well in both the training and the validation cohorts, and decision curve analyses showed that the model had good clinical applicability. CONCLUSION: The prediction model developed in this study holds predictive value for short-term DR following BMS in patients with obesity and T2DM.