Risk factors and predictive modeling of early postoperative liver function abnormalities.

Area of Science:

• Anesthesiology and Perioperative Medicine
• Hepatology
• Surgical Outcomes Research

Background:

• Limited research exists on factors influencing postoperative abnormal liver function in non-hepatic and non-cardiac surgeries.
• Understanding these factors is crucial for improving patient outcomes and developing targeted interventions.

Purpose of the Study:

• To identify risk factors for early postoperative abnormal liver function across diverse surgical types.
• To develop and validate a predictive model for postoperative liver dysfunction.

Main Methods:

• Retrospective cohort study of 3720 patients from 5 surgical departments.
• Logistic regression and LASSO analysis identified risk factors; a prediction model was constructed.
• Model performance was assessed using the Hosmer-Lemeshow test and ROC curve analysis.

Main Results:

• Key predictors of abnormal liver function include elevated preoperative aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels, and reduced platelet counts.
• Intraoperative sevoflurane use was also identified as a significant risk factor.
• The developed prediction model showed strong predictive efficacy and good calibration.

Conclusions:

• Elevated preoperative liver enzymes, low platelet counts, and sevoflurane use are significant risk factors for postoperative liver injury.
• The established risk prediction model demonstrates robust efficacy in identifying patients at risk for liver dysfunction.