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Digital Early Warning System for Acute Lung Injury in Liver Surgery

RECRUITINGSponsored by Beijing Tsinghua Chang Gung Hospital
Actively Recruiting
SponsorBeijing Tsinghua Chang Gung Hospital
Started2024-11-01
Est. completion2027-06-01
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT07070362

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.

Eligibility

Age: 18 Years+Healthy volunteers accepted
Inclusion Criteria:

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

Conditions11

ARDS, HumanAcute Lung Injury(ALI)CancerLiver CancerLiver Cancer, AdultLiver CirrhosisLiver DiseaseLung CancerMASLDMASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis)

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Trial data from ClinicalTrials.gov. Trial status and eligibility can change — verify directly with the study contact or on ClinicalTrials.gov.

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