Preoperative Triglyceride-Glucose Index as a Predictor of Weight Loss Following Sleeve Gastrectomy: A Retrospective Cohort Study

The triglyceride-glucose (TyG) index is a simple and cost-effective surrogate marker of insulin resistance. While its role in predicting cardiometabolic risk is well established, its association with postoperative weight loss in bariatric surgery remains underexplored. This study aimed to evaluate the predictive value of the preoperative TyG index for weight loss outcomes following sleeve gastrectomy. In this retrospective cohort study, data from 122 patients who underwent laparoscopic sleeve gastrectomy between January 2019 and January 2024 at a tertiary care center were analyzed. Preoperative TyG index values were calculated using fasting glucose and triglyceride levels. Patients were grouped based on a TyG cut-off value determined by ROC analysis. Associations between the TyG index and postoperative weight loss—both in absolute (kg) and percentage terms—were assessed using Pearson correlation and multivariable linear regression. The mean TyG index was significantly higher in patients with greater postoperative weight loss (p < 0.05). ROC analysis identified a TyG cut-off of 8.7, which yielded a sensitivity of 75.4% and a specificity of 63.9% for predicting significant weight loss (AUC = 0.73). In multivariable analysis, the TyG index remained an independent predictor of postoperative weight loss after adjustment for age, sex, and BMI. Patients with TyG ≥ 8.7 demonstrated significantly higher absolute and percentage weight loss compared to those below this threshold. The preoperative TyG index is independently associated with postoperative weight loss outcomes in patients undergoing sleeve gastrectomy. Its ease of calculation and accessibility support its potential role as an adjunctive metabolic marker in preoperative counseling and risk stratification, rather than as a standalone tool for surgical decision-making. Prospective, multicenter studies are warranted to validate these findings and to clarify the clinical applicability of TyG-based thresholds.