Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 10,000
- 试验地点
- 1
- 主要终点
- Complication after surgery
研究概览
简要总结
This Study aims to develop machine learning models with the ability to predict patients' BMI and complications after Bariatric Surgery (CABS-Score).
This Study also aims to develop machine learning models with the ability to predict diabetic (DM II)patients' remission rate after Bariatric Surgery.
The service mentioned above will be publicly available as a web-based application
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients undergoing bariatric surgery
- •Patients >18 years
排除标准
- •Patients <18 years
- •Patients who cannot be followed up on for more than 6 month after surgery
- •Patients who are unable to provide informed approval to participate according to each centre's rules will be excluded.
结局指标
主要结局
Complication after surgery
时间窗: [Time Frame: From index surgery up to 3 months postoperatively]
Body mass Index (KG/m2) after surgery
时间窗: [Time Frame: From index surgery up to 1 year postoperatively]
Diabetes mellitus type II remission rate postoperatively
时间窗: [Time Frame: From index surgery up to 2 year postoperatively]
次要结局
未报告次要终点
研究者
Dr. Med Anas Taha
Research Fellow
University of Basel