Validation of the Prognostic Impact of a Retinal Photograph-based Cardiovascular Disease Risk Stratification System in de Novo HFrEF
NCT ID: NCT06978998
Last Updated: 2025-05-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
100 participants
OBSERVATIONAL
2024-12-10
2030-12-10
Brief Summary
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In this context of therapeutic uncertainty and prognostic heterogeneity, there is a critical need for novel, non-invasive risk stratification tools. Retinal imaging offers a unique advantage, enabling direct, in vivo visualization of systemic microvascular and neurovascular integrity. Prior work from our group has demonstrated that deep learning algorithms applied to retinal fundus photographs can estimate physiologic and metabolic markers-including CAC scores-and predict future cardiovascular events. The Reti-CVD scoring system, derived from these models, has been externally validated in independent populations.
In the present study, we aim to evaluate the prognostic utility of the Reti-CVD model in a cohort of patients with newly diagnosed HF and reduced ejection fraction. Specifically, we will assess whether retinal-derived risk scores at baseline are associated with adverse clinical outcomes, including cardiovascular events and all-cause mortality, and whether prognostic performance varies according to HF etiology."
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Detailed Description
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1. Eligible participants will be approached during outpatient visits or hospitalization. The purpose and procedures of the study will be explained in detail, and informed consent will be obtained prior to data collection. Even after initial enrollment, participants will undergo continuous re-confirmation of consent at each subsequent visit.
2. All data will be collected in accordance with clinical guideline of heart failure in Korea (published from KHFS). This includes demographic characteristics, clinical history, echocardiographic parameters, laboratory findings, and cardiovascular outcomes. These data will be documented in a dedicated case report form.
3. Participants will undergo assessments during the first year following enrollment, with a target total follow-up duration of at least five years to evaluate long-term clinical outcomes.
4. All study data will be stored on password-protected computers with restricted access. No personal identifiers will be included and only de-identified, coded data will be used for analysis to ensure data confidentiality. This study will not involve development or modification of a deep learning algorithm. Instead, we will apply a pre-existing, validated retinal-based cardiovascular risk classification algorithm to newly diagnosed heart failure patients. Prognostic analyses will be conducted to determine whether algorithm-derived risk stratification is associated with differences in clinical outcomes during follow-up."
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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De novo Heart Failure cohort
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Presence of extensive retinal diseases that significantly impair visualization of the retinal vasculature
* Decline to provide informed consent for study participation, including:
* Pregnant individuals
* Individuals lacking decision-making capacity
20 Years
ALL
No
Sponsors
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Yonsei University
OTHER
Responsible Party
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Locations
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Severance hospital
Seoul, , South Korea
Countries
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Facility Contacts
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Other Identifiers
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4-2024-1332
Identifier Type: -
Identifier Source: org_study_id
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