New model aims to predict heart failure death risk more accurately
NCT ID NCT07332520
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looked at medical records of 4,000 heart failure patients to see if combining routine blood tests (like NT-proBNP) with heart scan results (like fat density around the heart) can better predict who is at risk of dying within a year. The goal is to improve personalized risk assessment for different types of heart failure. No new treatments or patient contact were involved.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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4,000 people
The number who actually took part.
- Started
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Jan 2012
- Finished
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Jan 2025
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Adults diagnosed with chronic heart failure at the study center between 2012 and 2024.
- Ages
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: 1. Age ≥ 18 years. 2. Confirmed diagnosis of chronic heart failure. 3. Treated at the study center between January 1, 2012, and December 31, 2024. 4. Availability of both qualifying blood biomarker test results (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (echocardiography and/or cardiac CT) performed within a ±3-month window around the index encounter. Exclusion Criteria: 1. Heart failure primarily due to severe primary valvular disease, acute myocardial infarction, myocarditis, or pulmonary embolism. 2. End-stage renal disease requiring dialysis. 3. Clinical records or follow-up data are severely incomplete, precluding outcome assessment.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
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Other studies related to the condition(s) this trial covers.
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