Dataset from: "Prognostic Value of Dynamic Changes in Pulmonary Congestion During Exercise Stress Echocardiography in Heart Failure With Preserved Ejection Fraction"

BACKGROUND: Patients with heart failure (HF) with preserved ejection fraction (HFpEF) typically develop dyspnea and<br> pulmonary congestion upon exercise. Lung ultrasound is a simple diagnostic tool, providing semiquantitative assessment<br> of extravascular lung water through B-lines. It has been shown that patients with HFpEF develop B-lines upon submaximal<br> exercise stress echocardiography; however, whether exercise-induced pulmonary congestion carries prognostic implications<br> is unknown. This study aimed at evaluating the prognostic value of B-line assessment during exercise in patients with HFpEF.<br> METHODS: Sixty-one New York Heart Association class I to II patients with HFpEF underwent standard echocardiography,<br> lung ultrasound (28-scanning point method), and BNP (B-type natriuretic peptide) assessment during supine exercise<br> echocardiography (baseline and peak exercise). The primary end point was a composite of cardiovascular death or HF<br> hospitalization at 1 year.<br> RESULTS: B-lines, E/e′, and BNP significantly increased during exercise (P&lt;0.001 for all). By multivariable analysis, both peak<br> (hazard ratio, 1.50 [95% CI, 1.21–1.85], P&lt;0.001), and change (hazard ratio 1.34 [95% CI, 1.12–1.62], P=0.002) B-lines<br> were retained as independent predictors of outcome (hazard ratios per 1 B-line increment), along with BNP and E/e′ ratio.<br> Importantly, adding peak B-line on top of a clinical model significantly improved prognostic accuracy (C-index increase, 0.157<br> [0.056–0.258], P=0.002) and net reclassification (continuous net reclassification improvement, 0.51 [0.09–0.74], P=0.016),<br> with similar results for B-line change.<br> CONCLUSIONS: Detection of exercise-induced pulmonary congestion by lung ultrasound is an independent predictor of outcome<br> in patients with HFpEF; its use may help refining the routine risk stratification of these patients on top of well-established<br> clinical variables.