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  • Title: Utility of combination of cardiac magnetic resonance imaging and high-sensitivity cardiac troponin T assay in diagnosis of inflammatory cardiomyopathy.
    Author: Šramko M, Kubánek M, Tintěra J, Kautznerová D, Weichet J, Malušková J, Franeková J, Kautzner J.
    Journal: Am J Cardiol; 2013 Jan 15; 111(2):258-64. PubMed ID: 23102878.
    Abstract:
    We evaluated the clinical utility of cardiac magnetic resonance imaging (CMR) combined with a novel high-sensitivity troponin T assay (hs-cTnT) in the diagnosis of inflammatory cardiomyopathy. CMR, measurement of hs-cTnT, and endomyocardial biopsy were performed in 42 patients with dilated cardiomyopathy and a short-term history of heart failure (median 2 months, interquartile range 1 to 3.5). The patients were followed up for 25 ± 9 months for events. Endomyocardial biopsy revealed myocarditis in 15 subjects (36%). The sensitivity, specificity, and diagnostic accuracy of the individual CMR tissue parameters for myocardial inflammation was 40%, 96%, and 76% for early gadolinium enhancement, 87%, 44%, and 60% for late gadolinium enhancement, 47%, 89%, and 74% for pericardial effusion, and 67%, 85%, and 79% for any 2 of the criteria simultaneously, respectively. An assessment of myocardial edema on T(2)-weighted imaging and/or hs-cTnT assay were inadequate for the diagnosis. The extent of late gadolinium enhancement and increased hs-cTnT concentration were significant predictors of a composite end point of cardiac death, urgent heart transplantation, and hospitalization for worsening heart failure (hazard ratio 1.1, 95% confidence interval 1.0 to 1.2, per percentage of left ventricular mass; and hazard ratio 2.2, 95% confidence interval 1.4 to 3.5, per ln ng/L; p = 0.008 and p = 0.001, respectively). In conclusion, the results of the present study have demonstrated a modest performance for CMR and a limited use of the hs-cTnT assay in the diagnosis of inflammatory cardiomyopathy. Nonetheless, in these patients, CMR and/or hs-cTnT assessment seems to be useful for the prediction of the clinical outcome.
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