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Multicenter Study
. 2024 Aug;30(8):2258-2264.
doi: 10.1038/s41591-024-03140-1. Epub 2024 Jul 12.

An evidence-based screening tool for heart failure with preserved ejection fraction: the HFpEF-ABA score

Yogesh N V Reddy  1 , Rickey E Carter  2 , Varun Sundaram  3 , David M Kaye  4 , M Louis Handoko  5 , Ryan J Tedford  6 , Mads J Andersen  7 , Kavita Sharma  8 , Masaru Obokata  9 , Frederik H Verbrugge  10   11 , Barry A Borlaug  12
Affiliations
Multicenter Study

An evidence-based screening tool for heart failure with preserved ejection fraction: the HFpEF-ABA score

Yogesh N V Reddy et al. Nat Med. 2024 Aug.

Abstract

Heart failure with preserved ejection fraction (HFpEF) is under-recognized in clinical practice. Although a previously developed risk score, termed H2FPEF, can be used to estimate HFpEF probability, this score requires imaging data, which is often unavailable. Here we sought to develop an HFpEF screening model that is based exclusively on clinical variables and that can guide the need for echocardiography and further testing. In a derivation cohort (n = 414, 249 women), a clinical model using age, body mass index and history of atrial fibrillation (termed the HFpEF-ABA score) showed good discrimination (area under the curve (AUC) = 0.839 (95% confidence interval (CI) = 0.800-0.877), P < 0.0001). The performance of the model was validated in an international, multicenter cohort (n = 736, 443 women; AUC = 0.813 (95% CI = 0.779-0.847), P < 0.0001) and further validated in two additional cohorts: a cohort including patients with unexplained dyspnea (n = 228, 136 women; AUC = 0.840 (95% CI = 0.782-0.900), P < 0.0001) and a cohort for which HF hospitalization was used instead of hemodynamics to establish an HFpEF diagnosis (n = 456, 272 women; AUC = 0.929 (95% CI = 0.909-0.948), P < 0.0001). Model-based probabilities were also associated with increased risk of HF hospitalization or death among patients from the Mayo Clinic (n = 790) and a US national cohort across the Veteran Affairs health system (n = 3076, 110 women). Using the HFpEF-ABA score, rapid and efficient screening for risk of undiagnosed HFpEF can be performed in patients with dyspnea using only age, body mass index and history of atrial fibrillation.

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Conflict of interest statement

Competing Interests Statement

BAB receives research support from the National Institutes of Health (NIH) and the United States Department of Defense, as well as research grant funding from AstraZeneca, Axon, GlaxoSmithKline, Medtronic, Mesoblast, Novo Nordisk, and Tenax Therapeutics. Dr. Borlaug has served as a consultant for Actelion, Amgen, Aria, BD, Boehringer Ingelheim, Cytokinetics, Edwards Lifesciences, Eli Lilly, Janssen, Merck, and Novo Nordisk. BAB and SJA are named inventors (US Patent no. 10,307,179) for the tools and approach for a minimally invasive pericardial modification procedure to treat heart failure.

YNR receives research support from the National Institutes of Health (NIH), Sleep Number, Bayer, Merck and United pharmaceuticals.

MLH reported receiving grants from The Dutch Heart Foundation and educational, speaker, and consultancy fees from Novartis, Boehringer Ingelheim, AstraZeneca, Vifor Pharma, Bayer, Merck Sharp & Dohme, Abbott, Daiichi Sankyo, and Quin outside the submitted work.

RJT reports no direct conflicts of interest related to this manuscript. He is co-chair of the PH due to left heart disease task force for 7th World Symposium on Pulmonary Hypertension. He reports general disclosures to include consulting relationships with Abbott, Acorai, Aria CV Inc., Acceleron/Merck, Alleviant, CareDx, Cytokinetics, Edwards LifeSciences, Gradient, Lexicon Pharmaceuticals, Medtronic, and United Therapeutics. RJT serves on steering committee for Merck, Edwards, and Abbott as well as a research advisory board for Abiomed. He also does hemodynamic core lab work for Merck.

MJA reports no direct conflicts of interest related to this manuscript. He reports a consulting relationship with Johnson & Johnson.

FHV reports no direct conflicts of interest related to this manuscript. He reports a consulting relationship with Abbott Laboratories, Abiomed, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb Belgium, Daiichi-Sankyo, Menarini Benelux, MSD, Novartis Pharma, Novo Nordisk Pharma, Pfizer, Roche Diagnostics, & Qompium.

The remaining authors declare no competing interests.

Figures

Extended Data Figure 1:
Extended Data Figure 1:
Calibration plots in Derivation and Validation Cohort predicted probabilities of HFpEF by the HFpEF-ABA score are grouped by deciles and plotted against the actual prevalence of HFpEF in each decile in ambulatory derivation (A) and validation cohort (B).
Figure 1 –
Figure 1 –. Discrimination of HFpEF from non-cardiac dyspnea using the HFpEF-ABA score.
(A-D) Logistic regression derived receiver operating curves for discrimination of HFpEF from non-cardiac dyspnea in derivation (A) and validation cohorts (B,C,D) using HFpEF-ABA score derived probabilities.
Figure 2 –
Figure 2 –. Risk of HF hospitalization and death by HFpEF-ABA score
Kaplan Meier curves showing the risk of the composite of HF hospitalization or death (A) and its individual components (B,C) with HFpEF-ABA score predicted HFpEF probability >75%. Hazard ratios were calculated by Cox proportional model.
See this image and copyright information in PMC

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