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Multicenter Study
. 2013 Mar;24(4):639-46.
doi: 10.1681/ASN.2012100990. Epub 2013 Feb 28.

Pulmonary congestion predicts cardiac events and mortality in ESRD

Collaborators, Affiliations
Multicenter Study

Pulmonary congestion predicts cardiac events and mortality in ESRD

Carmine Zoccali et al. J Am Soc Nephrol. 2013 Mar.

Abstract

Pulmonary congestion is highly prevalent and often asymptomatic among patients with ESRD treated with hemodialysis, but whether its presence predicts clinical outcomes is unknown. Here, we tested the prognostic value of extravascular lung water measured by a simple, well validated ultrasound B-lines score (BL-US) in a multicenter study that enrolled 392 hemodialysis patients. We detected moderate-to-severe lung congestion in 45% and very severe congestion in 14% of the patients. Among those patients with moderate-to-severe lung congestion, 71% were asymptomatic or presented slight symptoms of heart failure. Compared with those patients having mild or no congestion, patients with very severe congestion had a 4.2-fold risk of death (HR=4.20, 95% CI=2.45-7.23) and a 3.2-fold risk of cardiac events (HR=3.20, 95% CI=1.75-5.88) adjusted for NYHA class and other risk factors. Including the degree of pulmonary congestion in the model significantly improved the risk reclassification for cardiac events by 10% (P<0.015). In summary, lung ultrasound can detect asymptomatic pulmonary congestion in hemodialysis patients, and the resulting BL-US score is a strong, independent predictor of death and cardiac events in this population.

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Figures

Figure 1.
Figure 1.
Kaplan–Meier survival analyses of all-cause mortality and fatal and nonfatal cardiac events according to the BL-US.
Figure 2.
Figure 2.
HRs (and 95% CIs) for all-cause mortality and fatal and nonfatal cardiac events of patients with BL-US>60 versus patients with BL-US<15 (reference group) according to the presence/absence of advanced age (>65 years), sex, diabetes, hypertension, smoking (current/past versus never smokers), and background CV comorbidities. Data were derived by Cox regression analyses fitted according to the presence/absence of each risk factor.

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