Cardiac Surgical Procedures, Cardiopulmonary Bypass, Multiple Organ Dysfunction Syndrome, Postoperative Complications, Systemic Inflammatory Response Syndrome
Conditions
Keywords
Ulinastatin, Cardiac Surgery, Cardiopulmonary Bypass, Machine Learning, Precision Medicine
Brief summary
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.
Interventions
DRUGulinastatin
The patient used ulinastatin during the operation and while hospitalized in the ICU, and received mechanical ventilation.
Sponsors
Beijing Anzhen Hospital
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| All-cause mortality | 30 days after the operation | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The incidence rate of MODS | 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. | 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. |
Countries
China
Outcome results
None listed