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Algorithm Predicting Intraoperative Changes in Cardiac Output Using Capnography

NCT07061548 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 2005

Last updated 2025-07-18

No results posted yet for this study

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.

Conditions

  • General Anesthesia Using Endotracheal Intubation

Interventions

OTHER

No Intervention: Observational Cohort

No intervention

Sponsors & Collaborators

  • Samsung Medical Center

    lead OTHER

Eligibility

Min Age
19 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-03
Primary Completion
2025-12-31
Completion
2025-12-31

Countries

  • South Korea

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07061548 on ClinicalTrials.gov