Technological integration in predicting hypoxemia risk for improved surgical outcomes in Type A aortic dissection

The integration of clinical variables into a technology-enhanced prediction model provides robust early warnings of postoperative hypoxemia risk. Implementing timely surgical interventions and refined intraoperative management can minimize adverse respiratory outcomes, improving recovery in AAD patients.

Authors

Lingguo Wang
Ji Cui (ORCID: https://orcid.org/0000-0001-8905-8513)
Xiaoying Xing
Yujie Wang (ORCID: https://orcid.org/0000-0002-0593-7439)
Lu Pan (ORCID: https://orcid.org/0000-0001-6564-0939)
Qinying Wang (ORCID: https://orcid.org/0000-0002-7444-1090)

Institutions

Shanxi Medical University (CN)
Shanxi Provincial People’s Hospital (CN)
Xi'an Jiaotong University (CN)

Publication Details

Journal: Technology and Health Care
Published: 2025-05-05
DOI: https://doi.org/10.1177/09287329251333557
Primary Topic: Aortic Disease and Treatment Approaches
Type: article
Field-Weighted Citation Impact: 0.00

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article

Technological integration in predicting hypoxemia risk for improved surgical outcomes in Type A aortic dissection

Lingguo Wang, Ji Cui, Xiaoying Xing, Yujie Wang et al.

May 5, 2025

Technology and Health Care

Aortic Disease and Treatment Approaches

article

Technological integration in predicting hypoxemia risk for improved surgical outcomes in Type A aortic dissection

Lingguo Wang, Ji Cui, Xiaoying Xing, Yujie Wang, Lu Pan, Qinying Wang

May 5, 2025article en

Abstract

The integration of clinical variables into a technology-enhanced prediction model provides robust early warnings of postoperative hypoxemia risk. Implementing timely surgical interventions and refined intraoperative management can minimize adverse respiratory outcomes, improving recovery in AAD patients.

Technology and Health CareVol. 33(5)

Shanxi Medical University (CN), Shanxi Provincial People’s Hospital (CN), Xi'an Jiaotong University (CN)

Openalex Percentile: Top 85%

Aortic Disease and Treatment Approaches

DOI Source OpenAlex

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