Bing Zhao, Feilong Wang, Yerui Bi, Lei Li, Yabin Xia, Yan Jin
Metabolic and bariatric surgery (MBS) plays an important role in the management of obesity and related metabolic disorders, particularly in patients who meet established surgical criteria. The field has transitioned from open procedures to laparoscopic surgery, and the current landscape includes multiple operations with distinct efficacy-risk profiles. Alongside established procedures such as sleeve gastrectomy (SG), newer approaches-such as endoscopic metabolic interventions and robot-assisted platforms-are being evaluated for their feasibility, safety, learning curve, and potential outcome benefits. However, important questions remain regarding long-term durability, complication patterns, revisional surgery, patient selection, cost-effectiveness. To map these developments, we screened PubMed literature up to March 10, 2026 using terms such as "metabolic and bariatric surgery" and "sleeve gastrectomy", with emphasis on the International Federation for Surgery and Other Therapies for Obesity (IFSO) and higher-level evidence when available. We then synthesize findings across surgical technique evolution, indications and complications, unresolved challenges, and future directions, including how artificial intelligence (AI) and machine learning (ML) may support perioperative risk prediction and individualized treatment planning. This work aims to support clinicians in tailoring MBS plans and to guide future research priorities.