Logistic regression-based risk prediction of aortic adverse remodeling following thoracic endovascular aortic repair in patients with aortic dissection

Abstract

BACKGROUND

Aortic adverse remodeling remains a critical complication following thoracic endovascular aortic repair (TEVAR) for Stanford type B aortic dissection (TBAD), significantly impacting long-term survival. Accurate risk prediction is essential for optimized clinical management.

AIM

To develop and validate a logistic regression-based risk prediction model for aortic adverse remodeling following TEVAR in patients with TBAD.

METHODS

This retrospective observational cohort study analyzed 140 TBAD patients undergoing TEVAR at a tertiary center (2019–2024). Based on European guidelines, patients were categorized into adverse remodeling (aortic growth rate > 2.9 mm/year, n = 45) and favorable remodeling groups (n = 95). Comprehensive variables (clinical/imaging/surgical) were analyzed using multivariable logistic regression to develop a predictive model. Model performance was assessed via receiver operating characteristic-area under the curve (AUC) and Hosmer-Lemeshow tests.

RESULTS

Multivariable analysis identified several strong independent predictors of negative aortic remodeling. Larger false lumen diameter at the primary entry tear [odds ratio (OR): 1.561, 95%CI: 1.197–2.035; P = 0.001] and patency of the false lumen (OR: 5.639, 95%CI: 4.372-8.181; P = 0.004) were significant risk factors. False lumen involvement extending to the thoracoabdominal aorta was identified as the strongest predictor, significantly increasing the risk of adverse remodeling (OR: 11.751, 95%CI: 9.841-15.612; P = 0.001). Conversely, false lumen involvement confined to the thoracic aorta demonstrated a significant protective effect (OR: 0.925, 95%CI: 0.614–0.831; P = 0.015). The prediction model exhibited excellent discrimination (AUC = 0.968) and calibration (Hosmer-Lemeshow P = 0.824).

CONCLUSION

This validated risk prediction model identifies aortic adverse remodeling with high accuracy using routinely available clinical parameters. False lumen involvement thoracoabdominal aorta is the strongest predictor (11.751-fold increased risk). The tool enables preoperative risk stratification to guide tailored TEVAR strategies and improve long-term outcomes.

Keywords: Thoracic endovascular aortic repair; Aortic dissection; Adverse remodeling; Risk prediction model; False lumen; Thoracoabdominal involvement; Endovascular repair; Logistic regression

Core Tip: This study developed and validated a logistic regression-based risk prediction model for aortic adverse remodeling following thoracic endovascular aortic repair (TEVAR) in patients with type B aortic dissection. The model, incorporating routinely available clinical and imaging variables, demonstrated high predictive accuracy (area under the curve = 0.968). Pan-aortic false lumen involvement was identified as the strongest predictor, increasing the risk of adverse remodeling by nearly 12-fold. This tool facilitates preoperative risk stratification to guide personalized treatment strategies and improve long-term outcomes after TEVAR.