Algorithm Predicting Intraoperative Changes in Cardiac Output Using Capnography
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age19-75
SponsorSamsung Medical Center
About this trial
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 criteria
Qualifiers
Elective surgery under general anesthesia
Adult patients (18 < age < 76)
Patients who were monitored invasive arterial blood pressure (waveform) and capnography (numeric)
Disqualifiers
Emergency surgery
Cardiovascular and thoracic surgery
Known Asthma and Chronic obstructive pulmonary disease (COPD)
Preoperative pulmonary function test (PFT) abnormality over moderate grade
Trial design
Treatments tested in this trial
- No Intervention: Observational Cohort
Treatment groups
2,005 Participants
are divided into 1 treatment groupSponsors and collaborators
Source ClinicalTrials.gov