Multiple automated machine-learning prediction models for postoperative reintubation in patients with acute aortic dissection: a multicenter cohort study
We have developed and validated a high-performing risk prediction model for postoperative reintubation in patients with AAD. It can provide valuable guidance to clinicians in predicting reintubation and in developing timely preventative measures.
Authors
- Minghui Xie
- Shuyu Wen (ORCID: https://orcid.org/0000-0002-2859-3659)
- Ying Zhou (ORCID: https://orcid.org/0000-0003-3577-4527)
- Weihua Qiao (ORCID: https://orcid.org/0000-0001-6664-7075)
- Long Wu
- Jianzhong Zhang (ORCID: https://orcid.org/0000-0001-7056-8206)
- Chao Zhang (ORCID: https://orcid.org/0000-0001-9044-3566)
- Xingjian Hu (ORCID: https://orcid.org/0000-0002-8554-6138)
- Nianguo Dong (ORCID: https://orcid.org/0000-0001-5575-7084)
- Yin Xu
- Zhu Zeng
- Junwei Zhang
Institutions
- Union Hospital (HK)
- Wuhan Center for Disease Control and Prevention (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-04-11
- DOI
- https://doi.org/10.3389/fmed.2025.1531094
- Citations
- 3
- Primary Topic
- Aortic Disease and Treatment Approaches
- Type
- article
- Field-Weighted Citation Impact
- 4.56
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China