Artificial Intelligence for Ulinastatin Responder Outcome & Risk Assessment in CPB (AURORA)
Development and Validation of an AI-Based Tool for Identifying Responders and Stratifying Risks in Ulinastatin Treatment in Cardiac Surgery: A Multicenter Real-world Study
This is a multicenter, retrospective, real-world observational study aimed at developing and validating an artificial intelligence-based tool for identifying ulinastatin treatment responders and risk stratification in cardiac surgery patients undergoing cardiopulmonary bypass (CPB).
Ulinastatin, a glycoprotein extracted from human urine, has shown potential benefits in reducing postoperative complications and inflammatory responses in cardiac surgery. However, evidence supporting its efficacy and optimal application in specific patient populations remains insufficient.
This study will collect clinical data from approximately 4 tertiary cardiac centers in China, including patients who underwent cardiac surgery with CPB. Using machine learning algorithms (such as weighted K-modes clustering and XGBoost), the study aims to: (1) construct a multicenter real-world database for cardiac surgery; (2) identify clinical characteristics associated with ulinastatin treatment response; (3) develop and validate an AI-based risk stratification tool to assist clinical decision-making. This study may provide evidence-based guidance for personalized perioperative anti-inflammatory treatment in cardiac surgery.
研究概览
研究类型
注册 (估计的)
联系人和位置
学习地点
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Beijing、中国
- Center for Cardiac Surgery and Critical Care
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参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
取样方法
研究人群
描述
Inclusion Criteria:
- Patients underwent extracorporeal circulation heart surgery, including coronary artery bypass grafting, valve repair or replacement surgery, congenital heart defect repair surgery, and major vascular and aortic disease surgeries;
- Patients received standard treatment (such as anticoagulation, circulatory support), with or without ulinastatin.
Exclusion Criteria:
- Patients who had undergone cardiopulmonary bypass surgery multiple times;
- Patients with incomplete clinical records, lacking key information such as patient ID, age, gender and disease diagnosis.
学习计划
研究是如何设计的？
设计细节
研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
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All-cause mortality
大体时间：30 days after the operation
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All-cause mortality occurring during the hospitalization period following cardiac surgery with cardiopulmonary bypass.
Mortality is defined as death from any cause that occurs from the time of surgery until hospital discharge, including deaths related to cardiovascular events, multiple organ dysfunction syndrome (MODS), infection, bleeding, or other complications.
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30 days after the operation
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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The incidence rate of MODS
大体时间：From the date of hospitalization until the date of hospital discharge or 30 days after the operation, whichever occurs first, assessed up to 30 days postoperatively.
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The number of new MODS cases occurring in the targeted patients during research time period, divided by the total number of individuals at risk over the same period.
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From the date of hospitalization until the date of hospital discharge or 30 days after the operation, whichever occurs first, assessed up to 30 days postoperatively.
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (实际的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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