Establishment of a Classification System and Postoperative Risk Warning Model for Patients Undergoing Bariatric Metabolic Surgery for Severe Obesity

Establishment of a Prospective Disease-Specific Follow-up Cohort of 2,000 Patients Based on the Following Inclusion and Exclusion Criteria All participants will undergo metabolic surgery. A prospective, disease-specific follow-up cohort will be established, and baseline data will be collected. Patients will be followed up at multiple postoperative time points: days 3 and 7, and months 1, 3, 6, 12, and 24. Follow-up assessments will include the occurrence of postoperative complications and adverse events, as well as the degree of metabolic improvement and prognosis. A multidimensional data platform will be used to integrate and analyze diverse indicators, identifying those strongly associated with postoperative adverse events. Clustering analysis will be applied to establish a classification system for patients undergoing metabolic surgery for severe obesity. Targeted assays will be performed on time-series biospecimens to identify novel risk biomarkers. A risk warning model will be constructed, validated, and evaluated. Finally, an intelligent digital system integrating patient classification and real-time risk alert functions will be developed to optimize long-term outcomes and enhance the precision and timeliness of classification and risk warning for healthcare professionals and patients.