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

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 to predict the risk of PMV (defined as mechanical ventilation >48 h) to help clinicians identify high-risk patients and improve outcomes. Methods: This retrospective study, designed and reported in accordance with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, 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 then developed using the retained predictors. Its performance was evaluated using receiver operating characteristic curves, calibration curves, decision curve analysis, and clinical impact curves. Results: Ten predictors were retained in the final model: age [odds ratio (OR) 1.036, 95% confidence interval (CI) 1.016-1.058, Conclusions: The nomogram effectively predicts the risk of PMV after ATAAD surgery, providing valuable insights for perioperative management and potentially improving patient outcomes.