A prospective diagnostic cohort study to evaluate the usefulness of AI-based heart failure diagnosis using a simple electrocardiogram acquisition device

A prospective diagnostic cohort study to evaluate the usefulness of AI-based heart failure diagnosis using a simple electrocardiogram acquisition device - usefulness of AI-based heart failure diagnosis

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000057871

Enrollment

100

Registered

2025-05-15

Start date

2023-03-15

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute heart failure

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients aged 20 years or older who visited a hospital with complaints of shortness of breath or leg edema

Exclusion criteria

Exclusion criteria: Patients who do not consent

Design outcomes

Primary

Measure	Time frame
Diagnostic accuracy of heart failure by HF index (sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, AUC)	—

Secondary

Measure	Time frame
Identification of factors affecting the diagnostic ability of the HF index for heart failure, diagnostic accuracy of the HF index for each of the heart failure pathological classifications (HFpEF, HFmrEF, HFrEF), severity (NYHA classification), and clinical scenario classifications, and diagnostic accuracy of NT-proBNP for heart failure	—

Countries

Japan

Contacts

Public ContactHIROSHI HORI

Minamiuonuma City Hospital Internal Medicine

ubm5134@mbr.nifty.com09061749328

Outcome results