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

NCT07093502 | Recruiting

• 1 other identifier: ThirdXiangyaR25017
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to establish a classification system for patients undergoing metabolic surgery for severe obesity by constructing a prospective cohort of 2,000 patients and collecting clinical and biological data at multiple time points before and after surgery. By analyzing clinical, laboratory, and multi-omics characteristics, the study will identify indicators associated with postoperative adverse events and develop a risk warning model using machine learning algorithms. Ultimately, an intelligent digital system will be developed based on the classification criteria and risk model, integrating surgical classification and risk alert functions to provide real-time feedback, supporting clinicians and patients in optimizing postoperative treatment and risk management.

Conditions

Obesity; Bariatric Surgery; Bariatric Surgery (Sleeve Gastrectomy )

Keywords

Severe obesity; bariatric surgery; Classification System; Postoperative Risk Warning Model

Outcome Measures

Primary Outcomes (2)

• Number of Participants Stratified into Distinct Clusters Using Unsupervised Clustering Algorithm Based on BMI, Comorbidity Count, Inflammatory Markers, and Proteomics Profiles

  Participants will be stratified at baseline using an unsupervised clustering algorithm (e.g., k-means) based on the following input variables:（1）Body mass index (BMI, kg/m²)；（2）Comorbidity count (number of chronic diseases at enrollment)；（3）Inflammatory markers (e.g., CRP in mg/L, IL-6 in pg/mL)；（4）Proteomics features (relative expression intensity from LC-MS) The clustering procedure will produce a categorical variable assigning each participant to one of 3-5 data-driven subtypes. The total number of participants in each subtype group will be reported.

  From enrollment to the end of follow-up at 2 years

• Accuracy, Sensitivity, and Specificity of the Postoperative Risk Prediction Model for Adverse Outcomes

  Model performance will be assessed for predicting postoperative adverse outcomes within 12 months after bariatric surgery. Predictors include demographic data, intraoperative parameters, early postoperative recovery data, and stratification subtype. Model discrimination will be evaluated using area under the receiver operating characteristic curve (AUC-ROC), and calibration will be assessed with calibration plots and Hosmer-Lemeshow test. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) will be reported using confusion matrix analysis in internal validation (e.g., bootstrapping or 10-fold cross-validation).

  Up to 24 months after surgery

Secondary Outcomes (1)

• User Satisfaction Score of the Digital Postoperative Management System Measured by System Usability Scale (SUS)

  At 24 months after initiation of digital system use

Eligibility Criteria

• Age: 18 Years - 50 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Patients undergoing bariatric/metabolic surgery

You may qualify if:

• Patients who meet the clinical indications for bariatric/metabolic surgery;
• Adults aged 18 to 50 years; ③ Stable body weight (change within ±5% over the past 3 months); ④ Undergoing either laparoscopic sleeve gastrectomy (LSG) or laparoscopic Roux-en-Y gastric bypass (LRYGB).

You may not qualify if:

• ① Patients with conditions affecting the immune or metabolic systems (e.g., endocrine disorders such as untreated hypothyroidism/hyperthyroidism, cancer);
• Patients with renal or hepatic impairment;
• Patients who have taken medications that may affect metabolism within the past 3 months (e.g., weight-loss drugs, asthma medications, psychiatric medications, corticosteroids);
• Patients who have previously undergone bariatric surgery and are undergoing revisional surgery; ⑤ Patients with psychiatric disorders, especially those with comorbid behavioral or personality disorders (e.g., binge eating disorder);
• Patients currently participating in other clinical studies that may conflict with this study or those who refuse to sign the informed consent form.

Sponsors & Collaborators

• The Third Xiangya Hospital of Central South University: lead

Study Sites (1)

Third Xiangya Hospital of Central South University

Changsha, Hunan, 410013, China

RECRUITING

Biospecimen

Retention: SAMPLES WITH DNA

Serum sample；Plasma sample；Adipose tissue；Gastric fundus tissue

MeSH Terms

Conditions

Obesity; Obesity, Morbid

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Liyong Zhu

CONTACT

+86 13975879453; zly8128@csu.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 15, 2025
• First Posted: July 30, 2025
• Study Start: April 1, 2025
• Primary Completion (Estimated): December 31, 2035
• Study Completion (Estimated): December 31, 2035
• Last Updated: July 30, 2025

Record last verified: 2025-07

Locations

CN (1)