Abstract

BackgroundWhile Reddy proposed the H2FPEF diagnostic algorithm to aid in diagnosing heart failure with preserved ejection fraction (HFpEF), certain parameters like age and obesity are not suitable for Asian population, especially given the increasing incidence of HFpEF in younger individuals. Therefore, this study aimed to develop an easy-to-use nomogram with non-invasive indices that can be used in outpatient clinics in Taiwan to quickly estimate the probability of HFpEF and help decide whether further invasive cardiopulmonary exercise test (CPET) is needed. MethodsOutpatients with unexplained dyspnea and fatigue were recruited divided into HFpEF (n = 64) and non-HFpEF (n = 34) groups based on invasive CPET and echocardiography. Multivariate logistic regression analyses identified independent noninvasive variables for developing an HFpEF nomogram. The nomogram's performance was assessed and validated using the concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis. ResultsMultivariate logistic regression analyses identified five independent noninvasive variables for developing an HFpEF nomogram, including dyslipidemia (OR = 5.264, p = 0.010), diabetes (OR = 3.929, p = 0.050), left atrial area (OR = 1.130, p = 0.046), hemoglobin <13 g/dL (OR = 5.372, p = 0.010), and NT-proBNP ≥245 pg/mL (OR = 5.108, p = 0.027). The nomogram showed good discriminatory ability (C-index = 0.842) and calibration performance (p = 0.873) and high net benefit (0.1−0.95). Notably, the HFpEF nomogram showed better diagnostic accuracy than the H2FPEF score model in predicting Taiwanese HFpEF patients (AUC: 0.873 vs. 0.608, p = 0.0006). ConclusionThe noninvasive HFpEF nomogram provides a preliminary estimation of the probability of HFpEF in Taiwanese outpatients with unexplained dyspnea and fatigue, which may help the decision-making on further invasive CPET.

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