FIND HF Risk-guided Screening for Heart Failure - Pilot Study

NCT07367841 | Not Yet Recruiting

• 2 other identifiers: FIND HF Pilot studyPG.25.12417
• Study Type: observational
• Target: 475
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this clinical trial is to learn if the FIND HF algorithm detection rates of heart failure during testing are higher amongst participants identified as high FIND-HF risk compared to those identified as low risk in a population identified as at risk of undiagnosed heart failure. The main questions it aims to answer are:

• Are people who are identified as high risk by the FIND-HF tool more likely to be diagnosed with heart problems during testing than those identified as low risk?
• Are people identified as high risk by the FIND-HF tool more likely to show signs of heart problems during testing than those identified as low risk?? Researchers will compare patients in the high risk and low risk groups to see if more patients are detected with asymptomatic heart failure in the high risk group compared to the low risk group. Participants will attend one visit at a local clinic where they will undergo an NT proBNP blood test which indicates heart failure and an echocardiogram to evaluate the heart's chambers, valves and overall function to help diagnose various heart conditions.

Conditions

Heart Failure

Keywords

Artificial Intelligence; Data Science; Health Inequalities; Heart Failure

Outcome Measures

Primary Outcomes (1)

• To determine whether detection rates of a composite of asymptomatic LVSD, HFrEF, HFmREF, or HFpEF during diagnostics are higher amongst participants identified as high FIND-HF risk compared to those identified as low risk

  Odds ratio of asymptomatic LVSD, HFrEF, HFmREF, or HFpEF detection rates from intervention in people identified as high HF risk compared with people identified as low HF risk

  Through study completion, an average of 12 months from date of enrolment

Secondary Outcomes (1)

• To determine if components of composite outcome during diagnostics are higher amongst participants identified as high FIND-HF risk compared to those identified as low risk

  Through study completion, an average of 12 months from date of enrolment

Study Arms (1)

Patients at risk of developing Heart Failure

Patients will attend one visit with a Cardiology specialist Clinical research fellow who will carry out tests to detect Heart Failure

Diagnostic Test: FIND HF algorithm

Interventions

FIND HF algorithm DIAGNOSTIC_TEST

Algorithm developed by the research team to identify patients at risk of heart failure that is currently undetected.

Patients at risk of developing Heart Failure

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients identified at risk of developing Heart Failure by the FIND HF algorithm and are aged 40 and over, living in the Yorkshire area.

You may qualify if:

• Registered with a doctor practice that uses electronic health system to record patient medical notes Age at enrolment greater or equal to 40 Identified as at risk of developing Heart Failure

You may not qualify if:

• Registered with a doctor practice that is participating in research studies relating to heart failure screening
• Known diagnosis of HF
• On the palliative care register
• Unable to give written informed consent for participation in the study
• Unable to adhere to the study requirements

Sponsors & Collaborators

• University of Leeds: lead

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Study Officials

• Chris P. Gale, Yes

  University of Leeds

  STUDY CHAIR

Central Study Contacts

Ramesh Nadarajah, Yes

CONTACT

+44 113 343 7000; ramesh.nadarajah@nhs.net

Catherine Reynolds, Yes

CONTACT

+44 113 343 7000; medcre@leeds.ac.uk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Cardiovascular Medicine

Study Record Dates

• First Submitted: September 30, 2025
• First Posted: January 26, 2026
• Study Start: February 1, 2026
• Primary Completion (Estimated): July 1, 2027
• Study Completion (Estimated): October 1, 2028
• Last Updated: January 26, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will not share