Developing and validating a pre-operative risk score to predict post-hepatectomy liver failure.

BACKGROUND

Post hepatectomy liver failure (PHLF) is a serious complication in patients undergoing liver resection. This study hypothesized that a new pre-operative risk score developed through statistical modeling to predict PHLF could be used to stratify patients at higher risk of PHLF.

METHODS

Patients who underwent hepatectomy between 2008 and 2016 were included in the derivation and validation cohorts. A multivariable binary logistic regression model was performed to identify predictors of PHLF, and a prognostic score was derived.

RESULTS

A total of 1269 patients were included in the derivation cohort. PHLF was encountered in 13.1% and was associated with significantly increased 90-day mortality and prolonged post-operative hospital stay (both p < 0.001). Multivariable analysis identified the extent of surgery (p < 0.001) and pre-operative bilirubin (p = 0.015), INR (p < 0.001), and creatinine (p = 0.048) to be independent predictors of PHLF. A risk score derived from these factors returned an area under the ROC curve (AUROC) of 0.816 (p < 0.001) for an internal validation cohort (N = 453), significantly outperforming the MELD score (AUROC: 0.643).

CONCLUSION

The PHLF risk score could be used to stratify the risk of PHLF among patients planned for hepatectomy.