Prediction Model of in Hospital Death for Stanford Type A Aortic Dissection Based on a Meta-analysis of 24 Cohorts.

Abstract

Aims: Patients with Stanford type A aortic dissection (TAAD) have high postoperative mortality. This study aimed to develop a prediction model for in-hospital death after surgery in patients with TAAD .

Methods: The derivation cohort came from a meta-analysis. Major risk factors were counted. The corresponding hazard ratio was reported to establish a prediction model for in-hospital death in patients with TAAD. Validation cohorts from 2 centres were used to evaluate the prediction model.

Results: The meta-analysis included 24 cohort studies with a total of 11404 patients and 1554 patients died early after surgery. Risk factors for the prediction model included age, body mass index, smoking, coronary heart disease, preoperative stroke, shock, preoperative cardiopulmonary resuscitation, pericardial tamponade and malperfusion. Patients with TAAD admitted to the First and the Fourth Hospital of Hebei Medical University between January 2020 and June 2024 were retrospectively collected. Patients from the 2 hospitals constituted validation cohorts A (n = 262) and B (n = 138). Risk scores were calculated for model validation and the prediction model demonstrated better differentiation for validation cohort A, with an area under the curve of 0.886 (95% confidence interval 0.842-0.931).

Conclusion: This study established a simple risk prediction model, including 13 risk factors, to predict in-hospital death in patients with TAAD. However, multi-center data is still needed to evaluate the prediction accuracy of the model.