Digital Early Warning System for Acute Lung Injury in Liver Surgery

Recruiting

• 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

• Registration Number: NCT07070362
• Lead Sponsor: Beijing Tsinghua Chang Gung Hospital

Brief 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.

Study Timeline

• Study Start: 2024-11-01
• Study First Submitted: 2025-06-11
• Status Verified: 2025-07
• Study First Submitted QC: 2025-07-08
• Last Update Submitted: 2025-07-08
• Study First Posted: 2025-07-17
• Last Update Posted: 2025-07-17
• Primary Completion: 2027-06-01
• Study Completion: 2027-11-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 4000

Inclusion Criteria

• Age ≥ 18 years
• Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.)
• Voluntary participation with signed informed consent

Exclusion Criteria

Not provided

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Occurrence of ALI within 7 Days after Surgery	Perioperative period (Perioperative): Refers to the entire process from the determination of surgical treatment to postoperative rehabilitation (e.g., from 1 day before surgery to 7 days after surgery).	Berlin Definition: 1. Onset: Acute exacerbation of known injury or new/worsening respiratory symptoms within 1 week.; 2. Chest Imaging (X-ray or CT): Bilateral pulmonary shadows not fully explained by exudation, atelectasis, or nodules.; 3. Pulmonary Edema Etiology: Respiratory failure not fully attributed to heart failure or fluid overload; if no related risk factors, objective tests (e.g., Doppler echocardiography) are needed to exclude hydrostatic pulmonary edema.; 4. Oxygenation Levels: Mild - With CPAP/PEEP \>5 cmH2O, 200 mmHg \< PaO2/FiO2 \< 300 mmHg; Moderate - With CPAP/PEEP \>5 cmH2O, 100 mmHg \< PaO2/FiO2 \< 200 mmHg; Severe - With CPAP/PEEP \>5 cmH2O, PaO2/FiO2 \< 100 mmHg.

Trial Locations

Locations (1)

Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine，Tsinghua University; 🇨🇳 Beijing, Beijing, China