A PERSONALIZED SURGICAL ALGORITHM FOR BARIATRIC MANAGEMENT OF METABOLIC SYNDROME: integration of clinical profiles and 3D gastroanatomical modeling - Khamdamov, I.B. (JOURNAL OF EDUCATION AND SCIENTIFIC MEDICINE, 2025)
Background: Outcomes of bariatric surgery in patients with metabolic syndrome (MetS) vary widely depending on the severity of insulin resistance, anatomical features, and the presence of comorbid conditions such as GERD. A standardized decision-making framework is lacking. Objective: To develop and clinically validate a personalized algorithm for selecting optimal bariatric procedures in patients with MetS, based on metabolic parameters, GERD status, and anatomical modeling. Methods: An eight-parameter scoring system was constructed, incorporating BMI, HbA1c, HOMA-IR, C-peptide, GERD grade, NAFLD presence, stomach axis (from CT), and gastric volume (via 3D modeling). The algorithm stratified patients into two categories: candidates for anti-reflux LSG and candidates for individualized OAGB with tailored limb length. The system was prospectively tested in 120 patients. Algorithm performance was validated by comparing 12-month outcomes with those from standard surgical planning. Results: Application of the algorithm resulted in improved alignment between preoperative phenotype and surgical method. Patients assigned procedures via the algorithm showed greater %EWL (85.1±6.2% vs. 77.0±7.5%, p<0.001), better reduction in HbA1c (–2.4±0.5% vs. –1.8±0.6%, p<0.01), and lower GERD recurrence (5.3% vs. 16.7%, p<0.05). ROC analysis demonstrated high predictive value (AUC 0.84) in forecasting postoperative metabolic success. Conclusion: An algorithm combining metabolic, reflux-related, and anatomical parameters enables individualized surgical planning in MetS patients and improves clinical outcomes. Its integration into bariatric workflows may enhance decision-making and risk stratification. Keywords: Metabolic syndrome, bariatric surgery, surgical algorithm, GERD, HOMA-IR, C-peptide, 3D anatomy.