Future Innovations in Novel Detection of Heart Failure FIND-HF

Heart Failure Clinical Trial

— FIND-HF  

Official title:

Predicting Incident Heart Failure From Population-based Nationwide Electronic Health Records: Protocol for a Model Development and Validation Study

Clinical Trial Details — Status: Enrolling by invitation

Administrative data

• NCT number: NCT05756127
• Other study ID #: FINDHF01
• Status: Enrolling by invitation
• Start date: April 1, 2023
• Est. completion date: January 2025

Study information

• Verified date: May 2023
• Source: University of Leeds
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Heart failure (HF) is increasingly common and associated with excess morbidity, mortality and healthcare costs. New medications are now available which can alter the disease trajectory and reduce clinical events. However, many cases of HF remain undetected until presentation with more advanced symptoms, often requiring hospitalisation. Earlier identification and treatment of HF could reduce downstream healthcare impact, but predicting HF incidence is challenging due to the complexity and varying course of HF. The investigators will use routinely collected hospital-linked primary care data and focus on the use of artificial intelligence methods to develop and validate a prediction model for incident HF. Using clinical factors readily accessible in primary care, the investigators will provide a method for the identification of individuals in the community who are at risk of HF, as well as when incident HF will occur in those at risk, thus accelerating research assessing technologies for the improvement of risk prediction, and the targeting of high-risk individuals for preventive measures and screening.

Recruitment information / eligibility

• Status: Enrolling by invitation
• Enrollment: 14000
• Est. completion date: January 2025
• Est. primary completion date: January 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 16 Years to 120 Years

Eligibility

Inclusion Criteria:

1. Aged 16 years and older

2. No history of heart failure

3. A minimum of one year follow up Exclusion Criteria: -

Related Conditions & MeSH terms

• Heart Failure

Intervention

Other:
• Observational - no intervention given
Observational - no intervention given

Locations

Country	Name	City	State
United Kingdom	University of Leeds	Leeds	West Yorkshire

Sponsors (2)

Lead Sponsor	Collaborator
University of Leeds	Japan Foundation for Aging and Health

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To develop and validate a for predicting the risk of new onset HF	Predictive factors will be identified using Read codes (diagnoses), All variables will be considered as potential predictors, and may include: sociodemographic variables: age, sex, ethnicity, index of multiple deprivation; lifestyle factors (e.g. smoking status, alcohol consumption);	Between 2nd Jan 1998 and 28 Feb 2022
Primary	To identify and quantify the magnitude of predictors of new onset HF	The proposed model can extract informative risk factors from EHR data. Specifically we will fit multivariable Cox proportional hazard models with backwards elimination approach to retain predictors of incident HF within each prediction window.	Between 2nd Jan 1998 and 28 Feb 2022