NCT06277414招募中不适用
Machine Learning for the Prediction of Post-Endoscopic Retrograde Cholangiopancreatography Complication Risk
The First Affiliated Hospital of University of South China1 个研究点 分布在 1 个国家目标入组 2,000 人开始时间: 2018年1月1日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 2,000
- 试验地点
- 1
- 主要终点
- Number of Participants with Pancreatitis
研究概览
简要总结
To develop effective preoperative and postoperative prediction models for postoperative complications of ERCP
详细描述
To develop effective preoperative and postoperative prediction models for postoperative complications of ERCP based on machine learning
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 90 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Routine ERCP patients
排除标准
- •Unwillingness or inability to consent for the study
- •Pregnant women or breastfeeding
- •current acute pancreatitis
结局指标
主要结局
Number of Participants with Pancreatitis
时间窗: 1 month
Typical abdominal pain, with the level of serum amylase increasing at least 3 times of the normal range within 24 hours after ERCP.
次要结局
- Number of Participants with Cholangitis(1 month)
- Number of Acute PEC(post-ERCP-cholecystitis )(1 month)
- Number of Participants with Perforation(1 month)
- Number of Participants with bile duct stents(1 month)
研究者
研究点 (1)
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