Study on Cardiac Output Evaluation Based on Wearable Monitoring Data
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Yutao Guo
- Phone Number: +86 13683176151
- Email: zhanghuiay08@sian.com
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- 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
Exclusion Criteria:
- Patients with pacemaker implantation
- No smartphone
- Currently participating in other clinical trials
- Lactating women
- Pregnant Women
- Unable to run and ride due to personal physical and external reasons (subjects participating in the exercise state cardiac output model study)
- Physical examination results in the past year have clear cardiovascular, metabolic, bone and joint related diseases that have exercise risk, or have diseases and related potential health risks confirmed by the self-examination form of physical status before exercise (participants in the exercise state cardiac output model study)
- No informed consent was obtained
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
cardiac output
Time Frame: From enrollment to the end of follow-up at 1 month
|
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.
|
From enrollment to the end of follow-up at 1 month
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Heart failure
Time Frame: From enrollment to the end of follow-up at 1 month
|
Heart failure symptoms, acute heart failure episodes, rehospitalization rates, and cardiovascular mortality
|
From enrollment to the end of follow-up at 1 month
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- HZKY-PJ-2024-57
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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