Study on Cardiac Output Evaluation Based on Wearable Monitoring Data
ConditionCardiac Output
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorNavy General Hospital, Beijing
About this trial
Based on the monitoring data of wearable devices, with cardiac output (CO) as the gold standard, this study intends to develop a non-invasive evaluation model of CO based on wearable data, and optimize the parameters to realize the cardiac capacity detection function in resting and exercise states on the wearable device.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Over 18 years old
Left ventricular ejection fraction (Left ventricular ejection fraction, LVEF) < 50%(200 subjects)
Left ventricular ejection fraction (Left ventricular ejection fraction, LVEF) ≥50% (100 subjects)
Able to use smart phones and operate wearable devices such as wristbands/watches
Disqualifiers
Patients with pacemaker implantation
No smartphone
Currently participating in other clinical trials
Lactating women
Trial population
Two hundred HF patients with an left ventricular ejection fraction (LVEF) of less than 50% and 100 normal cardiac function subjects with an LVEF of 50% or greater were enrolled
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Exercise
Other interventionCardiac output (CO) was measured after exercise intervention in patients with normal cardiac function
Treatment groups
No treatment groups listed
Trial outcomes
Primary outcomes
1
cardiac output
Taking cardiac function indicators such as cardiac output by echocardiography as the gold standard, using wearable device monitoring data（Photoplethysmographic pulse wave）, the resting state cardiac output artificial intelligence machine learning model was established, and the sensitivity, specificity, positive predictive value, negative predictive value, F1 score, diagnostic efficiency Area Under Curve (AUC), and the sensitivity, specificity, positive predictive value, negative predictive value, F1 score, diagnostic efficiency of the model were calculated. AUC), precision and precision-recall curves were used to evaluate the performance of the model.
Time frame
From enrollment to the end of follow-up at 1 monthSecondary outcomes
1
Heart failure
Heart failure symptoms, acute heart failure episodes, rehospitalization rates, and cardiovascular mortality
Time frame
From enrollment to the end of follow-up at 1 monthLocations
Sponsors and contacts
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Source ClinicalTrials.gov
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