Key result
Combining B-lines, NT-proBNP, and LAVI yields ~0.74 AUC for identifying HFpEF in acute heart failure.
Why the study?
Heart failure with preserved ejection fraction is often difficult to identify at the bedside because no single clinical, biochemical, or echocardiographic marker is sufficiently definitive.
Does a combined model of lung ultrasound B-lines, NT-proBNP, and LAVI improve the bedside identification of HFpEF in patients with acute decompensated heart failure?
Observational (n=220)
No
Does a combined model of lung ultrasound B-lines, NT-proBNP, and LAVI improve the bedside identification of HFpEF in patients with acute decompensated heart failure?
Effect estimate: AUC 0.737 (95% CI 0.664-0.808)
Combining lung ultrasound B-lines, NT-proBNP, and LAVI provides moderate discriminatory ability for bedside identification of the HFpEF phenotype in patients with acute decompensated heart failure.
May aid multimodal HFpEF screening in cohorts; leaves open clinical utility pending prospective validation.
Background Heart failure with preserved ejection fraction (HFpEF) is often difficult to identify at the bedside because no single clinical, biochemical, or echocardiographic marker is sufficiently definitive. Lung ultrasound B-lines, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and left atrial volume index (LAVI) reflect different aspects of congestion and cardiac remodeling. This study evaluated whether combining these routinely available parameters could improve simplified bedside identification of HFpEF. Methods This single-center prospective study included 220 patients hospitalized with acute decompensated heart failure at Xiangtan Central Hospital between January 2023 and December 2025. HFpEF was defined as left ventricular ejection fraction ≥ 50%, and patients with mildly reduced or reduced ejection fraction were classified as non-HFpEF. B-line score, NT-proBNP, LAVI, E/e′, body mass index, and atrial fibrillation status were recorded. Logistic regression, receiver operating characteristic curve analysis, and decision curve analysis were used to evaluate the performance and potential clinical utility of individual markers and combined models. Results Among 220 patients, 57 had HFpEF and 163 had non-HFpEF. Individual markers showed limited-to-moderate discriminatory ability, with AUCs of 0.680 for B-line score, 0.655 for log-transformed NT-proBNP, and 0.550 for LAVI. The three-marker model combining B-line score, log-transformed NT-proBNP, and LAVI achieved an AUC of 0.737, with a sensitivity of 71.9% and specificity of 69.3%. The full exploratory model further increased the AUC to 0.765. Decision curve analysis suggested that the combined models provided greater net benefit than treat-all and treat-none strategies across a clinically relevant range of threshold probabilities. Conclusions A combination of lung ultrasound B-lines, NT-proBNP, and LAVI showed moderate ability to distinguish patients with a preserved-ejection-fraction phenotype from those with lower LVEF among patients with acute heart failure. This approach should be interpreted as a bedside phenotype-characterization tool rather than a validated diagnostic model for confirming HFpEF.
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Peng et al. (2026) conducted an observational in Acute decompensated heart failure (n=220). Combination of lung ultrasound B-lines, NT-proBNP, and left atrial volume index (LAVI) vs. Individual markers alone was evaluated on Discrimination of heart failure with preserved ejection fraction (HFpEF) from non-HFpEF (AUC 0.737, 95% CI 0.664-0.808). A three-marker model combining lung ultrasound B-lines, log-transformed NT-proBNP, and left atrial volume index achieved an AUC of 0.737 for distinguishing HFpEF from non-HFpEF in acute heart failure.
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