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Aims/Background Patients with acute Stanford type A aortic dissection (ATAAD) face particularly high risks of prolonged mechanical ventilation and weaning failure due to the combined effects of surgical trauma, systemic inflammation, and multi-organ involvement. However, current weaning predictors are primarily derived from general cardiac surgery populations, leaving ATAAD-specific evidence limited. This study investigated the factors influencing postoperative mechanical ventilation weaning outcomes in ATAAD patients and constructed a prediction model. Methods We retrospectively analyzed 120 postoperative ATAAD patients requiring mechanical ventilation at Nanjing First Hospital between January 2020 and March 2022. Patients were categorized into a weaning success group (n = 79) and a weaning failure group (n = 41) based on their weaning outcomes. Clinical variables were compared between groups, and multivariate logistic regression analysis was performed to identify independent predictors of weaning failure. Multicollinearity was assessed using variance inflation factors (VIFs). A nomogram prediction model was developed, and its performance was evaluated using the C-index, receiver operating characteristic (ROC) curve analysis, calibration plots, and decision curve analysis (DCA). Results Multivariate logistic regression identified a history of chronic obstructive pulmonary disease (COPD) (p = 0.002), a history of kidney disease (p = 0.002), increased intraoperative blood loss (p = 0.037), elevated postoperative 24-hour serum creatinine (Scr) (p < 0.001), and elevated brain natriuretic peptide (BNP) levels (p = 0.009) as independent risk factors for weaning failure from mechanical ventilation in ATAAD patients. An increased respiratory rate (p = 0.003) was a protective factor. Multicollinearity testing revealed that VIF values for all six variables were <5 (1.018-1.050), indicating no significant collinearity. The nomogram model demonstrated good discrimination (C-index = 0.806, 95% confidence interval [CI]: 0.752-0.859; with an area under the curve [AUC] = 0.80 (95% CI: 0.72-0.88, p < 0.001), with a sensitivity of 92.13% and specificity of 67.86%. The calibration curve showed strong agreement with the ideal model. DCA indicated a significant net clinical benefit at thresholds above 0.2, confirming the clinical utility of the model. Conclusion Mechanical ventilation weaning failure is a frequent and clinically significant complication after ATAAD surgery. Its risk is associated with a history of COPD, a history of kidney disease, intraoperative blood loss, postoperative Scr, BNP, and respiratory rate. The constructed nomogram accurately predicts weaning outcomes, offering valuable support for individualized risk assessment and clinical decision-making in ATAAD patients.