A nomogram‐based model to predict postoperative transient neurological dysfunctions in patients receiving acute type A aortic dissection surgery

Abstract

AbstractThe purposes of this study were to develop and validate a nomogram for predicting postoperative transient neurological dysfunctions (TND) in patients with acute type A aortic dissection (AAAD) who underwent modified triple‐branched stent graft implantation. This retrospective study developed a nomogram‐based model in a consecutive cohort of 146 patients. Patient characteristics, preoperative clinical indices, and operative data were analyzed. Univariate and multivariable analyses were applied to identify the most useful predictive variables for constructing the nomogram. Discrimination and the calibration of the model was evaluated through the receiver operating characteristic curve (ROC), the Hosmer–Lemeshow goodness‐of‐fit test and the decision curve analysis (DCA). At the same time, to identify and compare long‐term cumulative survival rate, Kaplan‐Meier survival curve was plotted. The incidence rate of postoperative TND observed in our cohort were 40.9%. Supra‐aortic dissection with or without thrombosis, creatinine >115 μmol and albumin <39.7 g/L, selective antegrade cerebral perfusion (SACP) time >7 min and total operation time >303 min, were confirmed as independent predictors that enhanced the likelihood of TND. Internal validation showed good discrimination of the model with under the ROC curve (AUC) of 0.818 and good calibration (Hosmer–Lemeshow test, p > .05). DCA revealed that the nomogram was clinically useful. In the long‐term survival there was no significant difference between patients with or without TND history. The results showed the predict model based on readily available predictors has sufficient validity to identify TND risk in this population, that maybe useful for clinical decision‐making.