Trials / Recruiting
RecruitingNCT07070362
Digital Early Warning System for Acute Lung Injury in Liver Surgery
The Construction of a Digital Intelligence Early Warning System for the Whole Process of Acute Lung Injury in Liver Surgery Based on Cardiopulmonary Interaction Characteristics
- Status
- Recruiting
- Phase
- —
- Study type
- Observational
- Enrollment
- 4,000 (estimated)
- Sponsor
- Beijing Tsinghua Chang Gung Hospital · Academic / Other
- Sex
- All
- Age
- 18 Years
- Healthy volunteers
- Not accepted
Summary
This study focuses on developing an explainable machine learning model based on cardiopulmonary interaction characteristics to achieve early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will establish a digital early-warning system for ALI to provide support for clinical diagnosis and treatment decisions, thereby reducing the incidence and fatality rate of ALI.
Detailed description
This study will leverage cardiopulmonary interaction parameters to predict ALI in patients undergoing major liver surgery. Specifically, the research will collect data from preoperative, intraoperative, and postoperative phases. Machine learning algorithms-including logistic regression, random forest, support vector machines (SVM), and neural networks-will be used to develop and validate the prediction model. Model performance will be evaluated using metrics such as accuracy, sensitivity, specificity, and the receiver operating characteristic (ROC) curve. The ultimate objective is to develop a highly accurate and interpretable model that can be integrated into a digital early-warning system for clinical application.
Conditions
- Acute Lung Injury(ALI)
- Liver Cirrhosis
- ARDS, Human
- MASLD
- MASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis)
- NAFLD (Nonalcoholic Fatty Liver Disease)
- Liver Cancer, Adult
Interventions
| Type | Name | Description |
|---|---|---|
| OTHER | None-placebo | This observational cohort study is non-interventional. Perioperative treatment plans are made based on model - suggested results and anesthesiologists' thought processes, without adding new medicines for patients. |
Timeline
- Start date
- 2024-11-01
- Primary completion
- 2027-06-01
- Completion
- 2027-11-30
- First posted
- 2025-07-17
- Last updated
- 2025-07-17
Locations
1 site across 1 country: China
Source: ClinicalTrials.gov record NCT07070362. Inclusion in this directory is not an endorsement.