Clinical and prognostic correlates of pulmonary congestion in coronary computed tomography angiography data sets

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

BACKGROUND: Signs of pulmonary congestion obtained from cardiac computed tomography angiographic (coronary CTA) images have not previously been related to clinical congestion or outcome and the clinical value is, therefore, unknown. Our objective was to test the hypothesis that signs of pulmonary congestion predict clinical heart failure and adverse outcome in patients with myocardial infarction.

METHODS: Coronary CTA was performed before invasive treatment in 400 prospectively included patients with non ST segment elevation myocardial infarction in an observational study. Using a previously described chest computed tomography evaluation algorithm, patients were classified as having "no congestion", "mild to moderate congestion" or "severe congestion".

RESULTS: Using multivariate analyses, presence of pulmonary congestion on coronary CTA images was associated with age, female gender, left ventricular ejection fraction (LVEF) and left atrial size. The diagnostic accuracy for predicting clinical heart failure, defined as Killip class >1, was: sensitivity: 83%, specificity: 69%, positive predictive value: 25%, and negative predictive value: 97%. The median follow-up time was 50 months and the study end-point of death or hospitalization due to heart failure was reached in 68 (16%) patients. In a Cox proportional hazards model with adjustments for known risk factors and Killip class, the presence of "mild to moderate congestion" and "severe congestion" was independently associated with adverse outcome (Hazard ratio: 2.6 (95% CI:1.3-5.0) and 3.2 (1.3-7.5)).

CONCLUSION: Signs of pulmonary congestion on coronary CTA images are closely correlated to cardiac dysfunction, predict clinical heart failure, and provide prognostic value independent of LVEF and Killip class.

OriginalsprogEngelsk
TidsskriftJournal of Cardiovascular Computed Tomography
Vol/bind10
Udgave nummer6
Sider (fra-til)466-472
Antal sider7
ISSN1934-5925
DOI
StatusUdgivet - 2016

ID: 176953086