Preoperative HALP index as a predictor of in-hospital mortality after type A aortic dissection surgery: a retrospective cohort study.

OBJECTIVE

To evaluate the predictive value of the preoperative haemoglobin-albumin-lymphocyte-platelet (HALP) index for in-hospital mortality in patients undergoing cardiopulmonary bypass (CPB)-assisted type A aortic dissection surgery.

METHODS

This single-centre retrospective cohort study enrolled 750 adult patients who underwent type A aortic dissection surgery with CPB at a tertiary hospital from January 2021 to December 2025. The HALP index was calculated using preoperative laboratory data, with in-hospital mortality as the primary endpoint. Variables with p < 0.1 in univariate analysis were included in multivariate logistic regression to identify independent risk factors, and receiver operating characteristic (ROC) curves were used to assess the predictive performance of HALP and the combined model.

RESULTS

The in-hospital mortality rate was 12.8%. Patients in the mortality group had significantly lower HALP scores than survivors (49.27 ± 15.06 vs. 71.53 ± 25.98). Multivariate analysis identified age (OR = 1.06), chronic kidney disease (CKD) (OR = 2.71), reduced left ventricular ejection fraction (LVEF) (OR = 0.92) and low HALP (OR = 2.87) as independent predictors. ROC analysis showed that HALP (area under the curve (AUC) = 0.74) outperformed individual indicators (age, CKD, LVEF: AUC 0.60-0.65), and the combined model achieved the best predictive performance (AUC = 0.79).

CONCLUSIONS

The preoperative HALP index is an independent predictor of in-hospital mortality after type A aortic dissection surgery with CPB, with good discriminatory performance. As a simple and low-cost biomarker, it effectively supplements traditional risk scoring systems and supports preoperative risk stratification and clinical decision-making. Specifically, patients with low HALP values at admission may benefit from proactive blood product preparation, early nutritional support and intensified postoperative monitoring, thereby optimizing perioperative management and improving outcomes.