Real-Time Estimation of Arterial Partial Pressure of Carbon Dioxide in Patients Undergoing General Anesthesia: Predictive Modeling Study
The developed model provides more accurate and reliable estimates of PaCO2 than traditional ETCO2-based methods. This approach shows potential for facilitating real-time monitoring and timely clinical interventions. This study demonstrated the potential of artificial intelligence to enhance continuous monitoring of PaCO2; however, further validation, including prospective studies assessing clinical impact, is necessary.
Authors
- Ah Ra Lee (ORCID: https://orcid.org/0000-0003-1890-2443)
- Sooyoung Yoo (ORCID: https://orcid.org/0000-0001-8620-4925)
- Jun Ho Lee (ORCID: https://orcid.org/0000-0002-9424-8589)
- Ho‐Young Lee (ORCID: https://orcid.org/0000-0001-6518-0602)
- Hyun Ho Kim (ORCID: https://orcid.org/0000-0002-7379-6041)
Institutions
- Seoul National University Bundang Hospital (KR)
- Jeonbuk National University Hospital (KR)
- Jeonbuk National University (KR)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-09-16
- DOI
- https://doi.org/10.2196/64855
- Primary Topic
- Hemodynamic Monitoring and Therapy
- Type
- article
- Field-Weighted Citation Impact
- 0.00