Preoperative and intraoperative risk factors of postoperative stroke in total aortic arch replacement and stent elephant trunk implantation

Hao Jia; Ben Huang; Le Kang; Hao Lai; Jun Li; Chunsheng Wang; Yongxin Sun

doi:10.1016/j.eclinm.2022.101416

Preoperative and intraoperative risk factors of postoperative stroke in total aortic arch replacement and stent elephant trunk implantation

EClinicalMedicine. 2022 Apr 28:47:101416. doi: 10.1016/j.eclinm.2022.101416. eCollection 2022 May.

Authors

Hao Jia¹, Ben Huang¹, Le Kang¹, Hao Lai¹, Jun Li¹, Chunsheng Wang¹, Yongxin Sun¹

Affiliation

¹ Department of Cardiac Surgery, Zhongshan Hospital, Fudan University, 1069 Xietu Road, Shanghai 200032, China.

Abstract

Background: Acute type A aortic dissection (AAAD) is a disease with high mortality, for which total aortic arch replacement (TAAR) combined with stent elephant implantation (SETI) is a reliable surgical treatment; however, it is associated with a high incidence of postoperative stroke. This retrospective study aimed to find preoperative and postoperative risk factors for postoperative stroke in patients with TAAR combined with SETI, and to provide predictive models and single-factor threshold suggestions.

Methods: From October 2019 to March 2021, 229 AAAD patients who underwent TAAR and SETI were selected. Patients were divided into stroke group (n = 23) and non-stroke group (n = 206), and preoperative/intraoperative factors were evaluated by independent-samples T-test/ Mann-Whitney U test/Chi-Square test and odds ratio (OR) analysis. The Logistic regression equation and decision tree were used to construct the prediction model of the probability of postoperative stroke. Bayesian-learning model and 2-order derivation were used to calculate the inflection points of the continuous variables.

Findings: Platelet count (PLT), International normalised ratio (INR) value, presence of diabetic history, and cardiopulmonary bypass (CPB) time were independent predictors of postoperative stroke (P-value < 0.05), and the above four factors were used to construct the Logistic regression equation. As for the decision-tree model, a radical model with higher accuracy in stroke predicting was chosen. Three inflection points for the effect of continuous variables (PLT count = 60 × 10^9/L; INR value = 1.82; CPB time = 300 min) on postoperative stroke were found by 2-order derivation.

Interpretation: PLT count, INR value, presence of diabetic history, and CPB time were significant preoperative and intraoperative risk factors for postoperative stroke, and the identification and modeling of these factors can help us to take more active brain protection measures in high-risk patients.

Funding: YS was funded by the National Natural Science Foundation of China (Grant ID 81671942).

Keywords: AAAD, acute type A aortic dissection; Acute type A aortic dissection; CABG, coronary artery bypass grafting; CPB, cardiopulmonary bypass; CT, computed tomography; CTA, Computed tomographic angiography; CTP, computed tomographic perfusion imaging; DHCA, deep hypothermic circulatory arrest; OR, odds ratio; PLT, platelet count; Postoperative stroke; Predictive model; SETI, stent elephant trunk implantation; TAAR, Total aortic arch replacement; δrso2min, the lowest relative regional cerebral oxygen saturation to base‐line.