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.
調査の概要
研究の種類
入学 (推定)
連絡先と場所
研究場所
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Beijing、中国
- Center for Cardiac Surgery and Critical Care
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参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
サンプリング方法
調査対象母集団
説明
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.
研究計画
研究はどのように設計されていますか？
デザインの詳細
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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All-cause mortality
時間枠：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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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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The incidence rate of MODS
時間枠：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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協力者と研究者
スポンサー
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
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