Classification and real-time risk-warning system for people having bariatric metabolic surgery
Establishment of a Classification System and Postoperative Risk Warning Model for Patients Undergoing Bariatric Metabolic Surgery for Severe Obesity
This project will test whether clinical, lab, and biological data from 2,000 people having bariatric metabolic surgery can be used to classify patients and build a model that warns of postoperative risks.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2000 (estimated) |
| Ages | 18 Years to 50 Years |
| Sex | All |
| Sponsor | The Third Xiangya Hospital of Central South University Academic / other |
| Locations | 1 site (Changsha, Hunan) |
| Trial ID | NCT07093502 on ClinicalTrials.gov |
What this trial studies
The study will enroll a prospective cohort of 2,000 adults undergoing laparoscopic sleeve gastrectomy or Roux-en-Y gastric bypass and collect clinical, laboratory, and multi-omics samples before surgery and at multiple postoperative time points through 24 months. Researchers will integrate time-series biospecimens and clinical data on a multidimensional platform and use clustering and machine learning to identify features linked to postoperative adverse events. Targeted assays will seek novel biomarkers and a risk warning model will be developed, validated, and evaluated. The final aim is to implement an intelligent digital system that combines patient classification with real-time risk alerts to support clinicians and patients in postoperative management.
Who should consider this trial
Good fit: Adults aged 18–50 with clinical indications for bariatric/metabolic surgery, stable weight (±5% in the past 3 months), and planned laparoscopic sleeve gastrectomy or Roux-en-Y gastric bypass are ideal candidates.
Not a fit: People with untreated endocrine disorders, active cancer, significant renal or hepatic impairment, recent use of metabolism-altering medications, prior bariatric revisions, certain psychiatric or behavioral disorders, or those outside the age range may not benefit from the study's classification or risk model.
Why it matters
Potential benefit: If successful, the system could provide personalized, real-time risk alerts and help clinicians and patients reduce complications and optimize recovery after bariatric surgery.
How similar studies have performed: Existing risk models and cohorts for bariatric outcomes exist, but a large prospective multi-omics classification with an integrated real-time digital risk-alert system is relatively novel and not yet widely validated.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria:
* 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).
Exclusion Criteria:
* 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.
Where this trial is running
Changsha, Hunan
- Third Xiangya Hospital of Central South University — Changsha, Hunan, China (Recruiting)
Study contacts
- Study coordinator: Liyong Zhu
- Email: zly8128@csu.edu.cn
- Phone: +86 13975879453
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.