A Deep Learning Approach to Identify Patients With Full Stomach on Ultrasonography
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 800
- 试验地点
- 1
- 主要终点
- Diagnostic accuracy of the model
研究概览
简要总结
Preoperative gastric ultrasonography is a newly developed tool used to evaluate gastric content and volume in assessing perioperative aspiration risk and guide anaesthetic management. And then build up effective clinical predictive models for identification of full stomach, which can predict the high aspiration risk.
详细描述
Aspiration of gastric contents can be a serious anesthetic related complication. Preoperative fasting was a common practice to decrease perioperative aspiration risk. However，one of most important prescription of enhanced recovery after surgery protocols is the reduction of preoperative fasting time in opposition to the traditional recommendation of overnight fast. Gastric antral sonography prior to anesthesia may have a role in identifying patients at risk of aspiration. The aim of this study is to construct models using deep learning for identification of full stomach, which can predict the aspiration risk.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients undergoing surgery Age: 18~85 yeas ASA 1~3
排除标准
- •Diabetes mellitus Upper gastrointestinal pathology such as hiatus hernia, oesophageal cancer Prior surgery to upper GI On medication that may affect gastric emptying time Pregnancy
结局指标
主要结局
Diagnostic accuracy of the model
时间窗: 1 year
次要结局
未报告次要终点