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.
연구 개요
상태
개입 / 치료
연구 유형
등록 (추정된)
연락처 및 위치
연구 장소
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Beijing, 중국
- Center for Cardiac Surgery and Critical Care
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참여기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
샘플링 방법
연구 인구
설명
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.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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All-cause mortality
기간: 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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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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The incidence rate of MODS
기간: 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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공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (실제)
기본 완료 (실제)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .
ulinastatin에 대한 임상 시험
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Nanjing Medical UniversityWest China Hospital; Beijing Anzhen Hospital; The First Affiliated Hospital of Guangzhou... 그리고 다른 협력자들초대로 등록대동맥 박리 | 대동맥 박리 동맥류중국