Algorithm Predicting Intraoperative Changes in Cardiac Output Using Capnography

July 15, 2025 updated by: Heejoon Jeong, Samsung Medical Center

Development of an Artificial Intelligence Model for Predicting Intraoperative Changes in Cardiac Output Using Capnography During General Anesthesia

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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.

Study Type

Observational

Enrollment (Estimated)

2005

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Korea, Republic of
      • Seoul, Korea, Republic of, 06351
        • Recruiting
        • Samsung Medical Center
        • Contact:
        • Principal Investigator:
          • Heejoon Jeong, MD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patient who underwent surgery under general anesthesia in Samsung Medical Center, Seoul, South Korea

Description

Inclusion Criteria:

  • Elective surgery under general anesthesia
  • Adult patients (18 < age < 76)
  • Patients who were monitored invasive arterial blood pressure (waveform) and capnography (numeric)

Exclusion Criteria:

  • 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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
capnography-cardiac output cohort
Adult patients who underwent surgery under general anesthesia with capnography and invasive arterial blood pressure monitor
Other: No Intervention: Observational Cohort
No intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Predictability of algorithm
Time Frame: Every time points with interval of 5 minutes during surgery
The performance of the algorithm to predict whether cardiac output has decreased by more than 20% compared to 5 minutes ago. Predictability is estimated by area under the receiver-operating characteristic curve analysis.
Every time points with interval of 5 minutes during surgery

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Samsung Medical Center

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 3, 2025

Primary Completion (Estimated)

December 31, 2025

Study Completion (Estimated)

December 31, 2025

Study Registration Dates

First Submitted

July 2, 2025

First Submitted That Met QC Criteria

July 2, 2025

First Posted (Actual)

July 11, 2025

Study Record Updates

Last Update Posted (Actual)

July 18, 2025

Last Update Submitted That Met QC Criteria

July 15, 2025

Last Verified

July 1, 2025

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • SMC2025-06-120-001

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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