Data-Driven Phenotyping in Heart Failure With Preserved Ejection Fraction

Sponsor
Instituto Politécnico de Leiria
Study ID
NCT07429396
Status
Not Yet Recruiting

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Conditions

  • Heart Failure
  • Heart Failure With Preserved Ejection Fraction (HFPEF)
  • Heart Failure, Diastolic

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Study Details

The goal of this observational study is to learn how people with Heart Failure with Preserved Ejection Fraction (HFpEF) can be grouped into different "phenotypes" based on their clinical information. The researchers want to understand whether these groups have different health profiles and different responses during a cardiopulmonary exercise test (CPET). The main questions this study aims to answer are: * Can clinical data be used to identify meaningful HFpEF phenotypes? * Do these phenotypes match well-known HFpEF scores, such as the H2FPEF and Heart Failure Association Pre-test Assessment, Echocardiography and Natriuretic Peptide (HFA-PEFF) scores? * Do people in different phenotypes show different results on a CPET? Participants will: * Have their past clinical records reviewed if they were diagnosed with HFpEF at the Local Health Unit of the Leiria Region (ULS RL); * A smaller group will attend one visit to complete a CPET, which measures how the heart, lungs and muscles respond during exercise. This study includes adults aged 18 years or older who have HFpEF. The study does not involve any new treatments or experimental drugs.

Key Dates

First listed
Feb 24, 2026
Start date
Dec 1, 2026
Status verified
Feb 2026
Primary completion
Aug 1, 2027
Completion
May 31, 2028

Study Design

Enrollment
200 participants (estimated)

Arms

  • Arm: Observational HFpEF Cohort
    Single observational cohort including all adults with an established diagnosis of heart failure with preserved ejection fraction (LVEF ≥50%) who received care at the Local Health Unit of the Leiria Region (ULS RL) since September 2018. Clinical, biochemical, imaging, functional, and therapeutic information recorded during previous hospitalizations will be extracted for retrospective analysis. A subset of participants will later be invited to complete a single cardiopulmonary exercise test (CPET) according to the study protocol. Phenotypes (clusters) will be identified post-hoc using unsupervised machine-learning methods and are not predefined at the time of enrollment.

Primary Outcome Measure

Identification and characterization of HFpEF phenotypes using multimodal clustering analysis [ Time Frame: Up to December 2026 (completion of retrospective data collection and clustering analysis). ]

Central Contacts

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