Development and validation of a nomogram to predict postoperative delirium in type B aortic dissection patients underwent thoracic endovascular aortic repair

Objective: Postoperative delirium (POD) is a common postoperative complication after cardiovascular surgery with adverse outcomes. No prediction tools are currently available for assessing POD in the type B aortic dissection (TBAD) population. The purposes of this study were to develop and validate a nomogram for predicting POD among TBAD patients who underwent thoracic endovascular aortic repair (TEVAR). Methods: The retrospective cohort included 631 eligible TBAD patients who underwent TEVAR from January 2019 to July 2021. 434 patients included before 2021 were in the develop set; 197 others were in the independent validation set. Least absolute shrinkage and selection operator (LASSO) and logistic regression were applied to identify the most useful predictive variables for constructing the nomogram. Discrimination and the agreement of the model was assessed with the area under the receiver operating characteristic curve (AUC), Brier score and the Hosmer-Lemeshow goodness-of-fit test. The results were validated using a bootstrap resampling and the validation set. Results: The incidence rate of POD observed in the development and validation cohort were 15.0% and 14.2%, respectively. Seven independent risk factors, including age >= 60 years, syncope or coma, postoperative blood transfusion, atelectasis, estimated glomerular filtration rate (eGFR) < 80 ml/min/1.73 m(2), albumin < 30 g/L, and neutrophil to lymphocyte ratio, were included in the nomogram. The model showed a good discrimination with an AUC of 0.819 (95% CI, 0.762-0.876) in the developed set, and adjusted to 0.797 (95% CI, 0.735-0.849) and 0.791 (95% CI, 0.700-0.881) in the internal validation set and the external validation, respectively. Favorable calibration of the nomogram was confirmed in both the development and validation cohorts. Conclusion: The nomogram based on seven readily available predictors has sufficient validity to identify POD risk in this population. This tool may facilitate targeted initiation of POD preventive intervention for healthcare providers.