Study on Cardiac Output Evaluation Based on Wearable Monitoring Data

NCT06938893 | Not Yet Recruiting DMC

• 1 other identifier: HZKY-PJ-2024-57
• Study Type: observational
• Target: 300
• Locations: 0 countries
• Sites: N/A

Brief Summary

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.

Conditions

Cardiac Output

Outcome Measures

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.

  From enrollment to the end of follow-up at 1 month

Secondary Outcomes (1)

• Heart failure

  From enrollment to the end of follow-up at 1 month

Interventions

Exercise OTHER

Cardiac output (CO) was measured after exercise intervention in patients with normal cardiac function

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study 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

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Navy General Hospital, Beijing: lead

MeSH Terms

Interventions

Exercise

Intervention Hierarchy (Ancestors)

Motor Activity; Movement; Musculoskeletal Physiological Phenomena; Musculoskeletal and Neural Physiological Phenomena

Central Study Contacts

Yutao Guo

CONTACT

+86 13683176151; zhanghuiay08@sian.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Month
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 17, 2025
• First Posted: April 22, 2025
• Study Start: April 20, 2025
• Primary Completion (Estimated): November 30, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: April 22, 2025

Record last verified: 2025-04