Digital Early Warning System for Acute Lung Injury in Liver Surgery

Recruiting now · Has a placebo group

Conditions studied: 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

In brief

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.

Key facts

Study ID

NCT07070362

Run by

Beijing Tsinghua Chang Gung Hospital

People needed

4000

Starts

2024-11-01

Expected to finish

2027-11-30

Last updated by the study team

2025-07-17

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

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

Where it is running

• Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine，Tsinghua University — Beijing, Beijing Municipality, China (enrolling)

Full record on ClinicalTrials.gov

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