Trials / Recruiting
RecruitingNCT07061548
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
- Status
- Recruiting
- Phase
- —
- Study type
- Observational
- Enrollment
- 2,005 (estimated)
- Sponsor
- Samsung Medical Center · Academic / Other
- Sex
- All
- Age
- 19 Years – 75 Years
- Healthy volunteers
- Not accepted
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.
Detailed description
Anesthesiologists strive to maintain adequate cardiac output during surgery. However, conventional monitoring of cardiac output requires an invasive procedure (risk) and an additional device (cost). Because most surgeries are performed without any invasive monitors, anesthesiologists must manage the patients without cardiac output information. However, modern anesthesia machines usually provide capnography, and continuous capnography monitoring can help estimate changes in cardiac output. Therefore, investigators aim to develop an artificial intelligence algorithm to predict intraoperative changes in cardiac output using capnography in patients undergoing surgery under general anesthesia. Investigators train a model using capnography data (5-minute duration) related to a 20% or greater decrease in cardiac output during the same period. The developed model can provide an alarm for a decrease in cardiac output based on the change in capnography.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| OTHER | No Intervention: Observational Cohort | No intervention |
Timeline
- Start date
- 2025-07-03
- Primary completion
- 2025-12-31
- Completion
- 2025-12-31
- First posted
- 2025-07-11
- Last updated
- 2025-07-18
Locations
1 site across 1 country: South Korea
Source: ClinicalTrials.gov record NCT07061548. Inclusion in this directory is not an endorsement.