Prediction of Sepsis in Patients Undergoing Abdominal Surgery: A Prospective, Observational Clinical Study
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 发起方
- 入组人数
- 55
- 试验地点
- 2
- 主要终点
- Accuracy of AI-Driven Sepsis Prediction in Postoperative Period
研究概览
简要总结
The goal of this prospective observational study is to develop and utilize an Artificial Intelligence (AI) model for the prediction of postoperative sepsis in patients undergoing abdominal surgery. The main questions it aims to answer are:
- Can a remote AI-driven monitoring system accurately predict sepsis risk in postoperative patients?
- How effectively can this system integrate and analyze multimodal data for early sepsis detection in the surgical ward?
Participants are equipped with non-invasive PPG-based wearable devices to continuously monitor vital signs and collect high-quality clinical data. This data, along with demographic and laboratory information from the Electronic Health Record (EHR) of the hospital, are used for AI model development and validation.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 120 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients undergoing elective abdominal surgery.
- •Postoperative admission to the surgical ward.
- •Age 18 years or older, who are able and willing to participate and have given written consent.
- •On admission, the primary investigator assess their risk to deteriorate during the first 72 hours after admission as reasonably high.
排除标准
- •<18 years of age Known allergy or contraindication to the monitoring devices.
- •Pre-existing conditions that could interfere with the study (e.g., chronic sepsis, immunodeficiency disorders).
- •Day case surgery.
- •Pregnancy.
- •Immediate transfer to ICU postoperatively.
- •Patient refusal or unable to give written consent.
结局指标
主要结局
Accuracy of AI-Driven Sepsis Prediction in Postoperative Period
时间窗: The accuracy of sepsis prediction will be assessed from the day of surgery, assessed daily for up to 7 days post-surgery or until hospital discharge.
This primary outcome measure evaluates the accuracy of an AI-driven monitoring system in predicting postoperative sepsis among patients undergoing abdominal surgery. The measure focuses on the system's ability to correctly identify sepsis, considering sensitivity, specificity, and predictive values.
次要结局
未报告次要终点