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Recruiting NCT07061548

Algorithm Predicting Intraoperative Changes in Cardiac Output Using Capnography

— Observational General Anesthesia Using Endotracheal Intubation

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: No Intervention: Observational Cohort.
Who it may be relevant to
Registry conditions: General Anesthesia Using Endotracheal Intubation. Basic parameters: 19 years — 75 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
South Korea
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

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

Overview

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.

Interventions

  • Other No Intervention: Observational Cohort
    No intervention

Primary outcome measures

  • Predictability of algorithm [Time frame: Every time points with interval of 5 minutes during surgery]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

South Korea · 1 center
  • Samsung Medical Center — Seoul

Identifiers

NCT: NCT07061548 · SMC2025-06-120-001

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗