Risk factors and predictive modeling of early postoperative liver function abnormalities

Research has shown that several factors can influence postoperative abnormal liver function; however, most studies on this issue have focused specifically on hepatic and cardiac surgeries, leaving limited research on contributing factors in other types of surgeries.

To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.

This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine. Patients were divided into abnormal (n = 108) and normal (n = 3612) groups based on liver function post-surgery. Univariate analysis and LASSO regression screened variables, followed by logistic regression to identify risk factors. A prediction model was constructed based on the variables selected via logistic regression. The goodness-of-fit of the model was evaluated using the Hosmer-Lemeshow test, while discriminatory ability was measured by the area under the receiver operating characteristic curve. Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.

The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery, as well as the sevoflurane use during the procedure, among others.

The above factors collectively represent notable risk factors for postoperative liver function injury, and the prediction model developed based on these factors demonstrates strong predictive efficacy.