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Heart Failure Risk and Events in People With HIV: The Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE)
Gerald S Bloomfield1,2, Maya Watanabe3, Sara McCallum4
1Department of Medicine and Duke Clinical Research Institute, Duke University, Durham, NC (G.S.B., P.S.D.).
People with HIV face higher heart failure risks, influenced by demographics and region. Observed heart failure events in people with HIV align with predicted risk scores, aiding future prevention strategies.
Area of Science:
- Cardiology
- Infectious Diseases
- Epidemiology
Background:
- People with HIV (PWH) have increased heart failure (HF) risk from traditional and HIV-related factors.
- HF incidence and risk prediction in PWH require further characterization.
- This study quantifies HF event risk in a global PWH cohort with low-to-moderate cardiovascular disease risk.
Purpose of the Study:
- To determine the incidence of heart failure (HF) events in people with HIV (PWH).
- To identify demographic, clinical, and HIV-specific factors associated with HF risk in PWH.
- To evaluate the consistency of observed HF events with predicted risk scores in PWH.
Main Methods:
- Analysis of 7769 participants from the REPRIEVE trial across 5 global regions.
- HF events were adjudicated through hospitalization records and standardized queries.
- HF incidence was calculated per 1000 person-years and stratified by various factors.
Main Results:
- HF incidence was 1.65 per 1000 person-years.
- Higher HF incidence observed in women, Black participants in high-income regions, those in sub-Saharan Africa, and individuals with hypertension or obesity.
- CD4+ T-cell count and HIV-1 RNA levels were not associated with HF incidence.
- Observed HF events (n=67) were consistent with predicted events (n=73) based on the Predicting Risk of Cardiovascular Disease Events HF score.
Conclusions:
- Demographics, clinical factors, and geographic region significantly influence HF incidence in PWH.
- The overall observed number of HF events in PWH aligns with predicted risk rates, validating risk assessment tools.
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