Development and external validation of a nomogram to predict prolonged postoperative mechanical ventilation in patients with acute type A aortic dissection

Abstract Background: Prolonged mechanical ventilation (PMV) significantly affects outcomes in patients undergoing acute type A aortic dissection (ATAAD) surgery. This study aimed to develop a nomogram for predicting the risk of PMV (defined as mechanical ventilation >48 hours) to help clinicians identify high-risk patients and improve outcomes. Methods: This retrospective study included 479 ATAAD patients from the First Affiliated Hospital of Anhui Medical University (training set) and 120 patients from Beijing Anzhen Hospital of Capital Medical University (validation set). Potential predictors were selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression. A nomogram was developed with significant predictors. Its performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results: Ten independent risk factors for PMV were identified: age (OR: 1.036, 95% CI: 1.016-1.058, P