{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T11:05:30Z","timestamp":1789211130950,"version":"build-2803163510"},"reference-count":69,"publisher":"BMJ","issue":"2","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"unspecified","delay-in-days":72,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["203135\/Z\/16\/Z"],"award-info":[{"award-number":["203135\/Z\/16\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["214321\/Z\/18\/Z"],"award-info":[{"award-number":["214321\/Z\/18\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001322","name":"South African Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001322","id-type":"DOI","asserted-by":"publisher"}]},{"name":"South African Research Chairs Initiative of the Department of Science and Innovation and National Research Foundation (NRF) of South Africa","award":["Grant No 64787"],"award-info":[{"award-number":["Grant No 64787"]}]},{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV 052110"],"award-info":[{"award-number":["INV 052110"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Heart Lung and Blood Institute (NHLBI), National Institutes of Health","award":["R01HL160437"],"award-info":[{"award-number":["R01HL160437"]}]},{"name":"Fogarty International Center of the National Institutes of Health and the Eunice Kennedy Shriver National Institute of Child Health & Human Development","award":["D43 TW010559"],"award-info":[{"award-number":["D43 TW010559"]}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Open Heart"],"accepted":{"date-parts":[[2026,8,25]]},"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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 \u226540 years (1008 PWH on ART \u22651 year and 500 people without HIV (PWoH)) at a primary care clinic in South Africa.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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\u2019 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  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