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Digital Early Warning System for Acute Lung Injury in Liver Surgery

RecruitingN/A

Sponsor: Beijing Tsinghua Chang Gung Hospital

Conditions: Acute Lung Injury(ALI), Liver Cirrhosis, ARDS, Human, MASLD, MASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis)

Countries: China

This study aims to develop an explainable machine learning model that takes into account the characteristics of cardiopulmonary interactions. This model will enable early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will create a digital early-warning system for ALI, thereby supporting clinical diagnosis and treatment decisions. This, in turn, should help reduce the incidence and mortality rates associated with ALI.

Eligibility overview

Sex: ALL

Age: 18 Years to —

Healthy volunteers: No

Study type: OBSERVATIONAL

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

Locations (4)

Beijing, Beijing Municipality, China
Beijing, China
Chongqing, China
Qingdao, China