Digital Early Warning System for Acute Lung Injury in Liver Surgery
Recruiting
Observational Study
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
No Placebo Group
Every participant receives an active treatment — no one gets a placebo.
No Study Drug
Researchers observe your health over time — no experimental treatment is given.
At a Glance
- Age
- 18 and older
- Sex
- Any
- Study type
- Observational
- Participants needed
- 4,000 (estimated)
- Sponsor
- Beijing Tsinghua Chang Gung Hospital · Other
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About This Trial
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…
Trial Locations
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Eligibility Criteria
Inclusion Criteria:
* Age ≥ 18 years
* Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.)
* Voluntary participation with signed informed consent
Contacts