{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:24:14Z","timestamp":1774542254373,"version":"3.50.1"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Surg."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To explore the risk factors for prolonged acute ventilation time after Stanford type A aortic dissection and to construct a nomogram prediction model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 178 patients with Stanford type A aortic dissection admitted to the Department of Cardiac and Vascular Surgery of the Affiliated Hospital of North Sichuan Medical College from 2020 to 2024 were retrospectively enrolled. The patients were randomly divided into a modeling group (124 cases) and a validation group (54 cases) at a 7:3 ratio. Risk factors for prolonged mechanical ventilation time after surgery were analyzed using univariate and multivariate logistic regression analysis, and a risk prediction model was constructed based on the results of multivariate logistic regression analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Multivariate logistic regression analysis showed that age, body mass index, preoperative oxygenation index, cardiopulmonary bypass time, and postoperative serum creatinine were risk factors for prolonged mechanical ventilation time after Stanford type A aortic dissection (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&amp;lt;\u20090.05).A risk prediction model was constructed based on these findings. The area under the ROC curve was 0.91 (95% CI: 0.86\u20130.97), with an accuracy of 0.88 (95% CI: 0.81\u20130.93), sensitivity of 0.92 (95%CI: 0.86\u20130.98), specificity of 0.82 (95%CI: 0.71\u20130.92), and an optimal cut-off value of 0.527. The results of model validation showed that the area under the ROC curve was 0.79 (95% CI: 0.66\u20130.92), with an accuracy of 0.72 (95%CI: 0.58\u20130.84), sensitivity of 0.77 (95%CI: 0.64\u20130.90), specificity of 0.6 (95%CI: 0.35\u20130.85).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The prediction model for prolonged mechanical ventilation time in patients with Stanford type A aortic dissection has a good prediction effect and is convenient for clinical use, providing a reference for medical workers to take preventive treatment.<\/jats:p>\n                  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