Development and validation of a novel prognostic score to improve prognostic prediction in patients with type B aortic dissection.

OBJECTIVE

Type B aortic dissection (TBAD) is a life-threatening aortic disease with an increasing incidence, which requires accurate risk stratification tools for thoracic endovascular aortic repair (TEVAR). This multicenter retrospective study aimed to enhance the risk prediction of severe adverse events post TEVAR in patients with TBAD by improving the Age, Creatinine, and Ejection Fraction (ACEF) score.

METHODS

This multicenter retrospective study enrolled 547 patients with TBAD who underwent TEVAR between 2015 and 2020. The training cohort (n = 382) from Fujian Medical University Union Hospital was used for model development, whereas the validation cohort (n = 165) from two external centers evaluated performance. Independent risk factors were identified using multivariate logistic regression. The novel composite risk score (ACEF-TBAD) combined age, creatinine, and ejection fraction with hypertension, D-dimer/fibrinogen ratio (DFR), and interleukin-6 (IL-6). Model performance was assessed using receiver operating characteristic curve, calibration curves, decision curve analysis, and reclassification indices.

RESULTS

The ACEF-TBAD score demonstrated superior predictive accuracy compared with the original ACEF, modified ACEF, and EuroSCORE II models, with area under the curve values of 0.922 in the training dataset and 0.829 in the validation dataset. Key determinants included hypertension (odds ratio [OR], 4.84; 95% confidence interval [CI], 2.03-11.58; P < .001), DFR (OR, 1.30; 95% CI, 1.16-1.45; P < .001), ACEF score (OR, 4.05; 95% CI, 1.76-9.32; P = .001), and IL-6 (OR, 1.41; 95% CI, 1.11-2.32; P < .001). The score showed excellent calibration (P > .05) and net clinical benefit (decision curve analysis curve). Reclassification analysis revealed significant improvements in risk stratification (net reclassification index, 0.366 in training; 0.206 in validation). The survival curves clearly demonstrated that the ACEF-TBAD score effectively stratified patients into distinct risk categories, which underscores the clinical utility of the ACEF-TBAD score in predicting severe adverse events and supports its use in risk assessment for patients with TBAD.

CONCLUSIONS

The ACEF-TBAD score is a novel and simple risk-stratification tool. This enables early identification of high-risk patients, facilitating personalized treatment and improving patient outcomes.