Nomogram for Predicting Remission of Metabolic Syndrome 1 Year after Sleeve Gastrectomy Surgery in Chinese Patients with Obesity.

PURPOSE: Sleeve gastrectomy (SG) is a widely used and effective treatment for patients with obesity and comorbid metabolic abnormalities. No specialized tool is available to predict metabolic syndrome (MS) remission after SG. We presented a nomogram that evaluated the probability of MS remission in obese patients 1 year after SG. MATERIALS AND METHODS: Patients with preoperative MS who underwent SG were enrolled in this retrospective study. They were divided into a training set and a validation set. Multivariate logistic regression analysis was performed to identify independent predictors of MS remission, and these predictors were included in the nomogram. Receiver operating characteristic curve was used to evaluate discrimination. Calibration was performed with the Hosmer-Lemeshow goodness-of-fit test. The net benefits of the nomogram were evaluated using decision curve analysis (DCA). RESULTS: Three hundred and eighteen patients with a median age of 34.0 years were analyzed. A training set and a validation set with 159 individuals each were established. A combination of age, preoperative high-density lipoprotein cholesterol, elevated triglycerides and glycated hemoglobin level independently and accurately predicted MS remission. The nomogram included these factors. The discriminative ability was moderate in training and validation sets (Area under curve 0.800 and 0.727, respectively). The Hosmer-Lemeshow X2 value of the nomogram was 8.477 (P = 0.388) for the training set and 5.361 (P = 0.718) for the validation set, indicating good calibration. DCA showed the nomogram had clinical benefits in both datasets. CONCLUSION: Our nomogram could accurately predict MS remission in Chinese patients with obesity 1 year after SG.

Associations of change in body fat percentage with baseline body composition and diabetes remission after bariatric surgery.

OBJECTIVE: The objective of this study was to determine the role of body fat percentage (BFP) changes in diabetes remission (DR) and the association between baseline body composition and its changes after bariatric surgery. METHODS: We analyzed 203 patients with type 2 diabetes who underwent Roux-en-Y gastric bypass. Body composition was measured using a gold-standard-derived predictive equation and magnetic resonance imaging. Body composition changes were calculated as 100 × (baseline value - follow-up value)/baseline value. We verified the results in a laparoscopic sleeve gastrectomy cohort with 311 patients. RESULTS: Compared with non-remission patients in the Roux-en-Y gastric bypass cohort, those who achieved DR showed a higher baseline fat-free mass index (FFMI) and experienced the most significant changes in BFP (p < 0.001). In comparative analyses, BFP changes were significantly better than BMI changes in identifying short- and long-term DR. Linear regression analysis identified FFMI as the most significant baseline variable correlated with BFP changes (p < 0.001). Baseline BMI was positively correlated with changes in BFP but negatively correlated with changes in FFMI. These findings were replicated in the laparoscopic sleeve gastrectomy cohort. CONCLUSIONS: BFP changes determine DR after bariatric surgery, and baseline FFMI is crucial for BFP changes. A low initial BMI is associated with a smaller BFP reduction and greater FFMI loss after bariatric surgery.