Liver Failure After Operative Procedure
Conditions
Brief summary
Post-hepatectomy liver failure (PHLF) is the leading cause of morbidity and mortality following major hepatectomy. Existing prediction models fail to capture the dynamic liver regeneration and perioperative changes, limiting their predictive accuracy. We aimed to develop a machine learning (ML) modelling system (PILOT architecture) integrating liver regeneration biomarkers with time-phased perioperative clinical data to accurately predict PHLF risk.
Interventions
None listed
Sponsors
Shanghai 10th People's Hospital
Jinling Hospital, China
Shen Feng
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
Extensive hepatectomy in our hospital（≥ three Hepatic segment）
Exclusion criteria
Serious basic diseases Intolerable surgery Refuse to perform ICG test before operation
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Postoperative liver failure | 1-5 days after surgery |
Countries
China
Outcome results
None listed