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◆ Open heart2026-09-12

Development of a heart failure with preserved ejection fraction risk prediction score in primary care settings with a high HIV prevalence.

Frissiano Honwana, Julian Wolfson, Abdullahi M Ahmed, Zuofu Huang, Msimelelo Mgidlana, Olukayode Aremu, Zaayid Omar, Ntobeko Ntusi, Graeme Meintjes, Landon Myer, Jason V Baker, Mpiko Ntsekhe

一句话结论 · In one sentence

The nomogram-based score, developed using routine clinical information and point-of-care BNP, is practical, accessible and may support screening and identification of individuals at high HFpEF risk for targeted referral for diagnosis and care in a sub-Saharan African primary care setting with a high HIV prevalence.

原始摘要(英文原文)· Original abstract
BACKGROUND: Antiretroviral therapy (ART)-treated people with HIV (PWH) have increased risk of heart failure with preserved ejection fraction (HFpEF). The diagnosis of HFpEF relies on cardiac imaging and expertise and is challenging in primary care settings. Further, existing risk prediction tools do not account for HIV-related risk. We developed a practical HFpEF risk prediction tool using data from the Prevalence and Phenotype of HIV-HFpEF in South Africa, a cross-sectional observational study that enrolled 1508 adults aged ≥40 years (1008 PWH on ART ≥1 year and 500 people without HIV (PWoH)) at a primary care clinic in South Africa. METHODS: We used four logistic regression models for HFpEF risk, including demographics, clinical factors, B-type natriuretic peptide (BNP) and ECG abnormalities. We compared the models' area under the receiver operating characteristic curve (AUC) with a random forest classifier, translated the final model into a nomogram-based risk score and evaluated its discrimination and calibration through bootstrap internal validation. RESULTS: The median age was 48 years, 77% female, 42% obese, 38% had hypertension and 7.8% met HFpEF criteria (118 participants; 85 (8.4%) among PWH and 33 (6.6%) among PWoH). Two logistic regression models outperformed the random forest classifier. The model that was used for the nomogram included age, sex, HIV status, smoking, hypertension, body mass index and BNP and showed good discrimination (overfitting-corrected AUC 0.77) with good calibration. CONCLUSIONS: The nomogram-based score, developed using routine clinical information and point-of-care BNP, is practical, accessible and may support screening and identification of individuals at high HFpEF risk for targeted referral for diagnosis and care in a sub-Saharan African primary care setting with a high HIV prevalence.
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Development of a heart failure with preserved ejection fraction risk prediction score in primary care settings with a high HIV prevalence. — 科研速览 Science Skim