Algorithm Predicting Intraoperative Changes in Cardiac Output Using Capnography
Development of an Artificial Intelligence Model for Predicting Intraoperative Changes in Cardiac Output Using Capnography During General Anesthesia
Samsung Medical Center
2,005 participants
Jul 3, 2025
OBSERVATIONAL
Conditions
Summary
Conventional monitoring of cardiac output requires an invasive procedure and an additional device, which can lead to increased risk and cost. Investigators developed an artificial intelligence algorithm to predict intraoperative changes in cardiac output using capnography in patients undergoing surgery under general anesthesia.
Eligibility
Inclusion Criteria3
- Elective surgery under general anesthesia
- Adult patients (18 < age < 76)
- Patients who were monitored invasive arterial blood pressure (waveform) and capnography (numeric)
Exclusion Criteria5
- Emergency surgery
- Cardiovascular and thoracic surgery
- Known Asthma and Chronic obstructive pulmonary disease (COPD)
- Preoperative pulmonary function test (PFT) abnormality over moderate grade
- Intraoperative monitoring duration less than 30 minutes
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Interventions
No intervention
Locations(1)
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NCT07061548