Aims: Guidelines recommend evaluation of family members of sudden cardiac death victims. However, initiation of cascade screening in families with uncertain diagnoses is not cost-effective and may cause unnecessary concern. For these reasons, we set out to assess to what extent cardiac magnetic resonance imaging (CMR) would increase the diagnostic precision and thereby possibly change the indication for family screening in patients with ventricular tachyarrhythmias.
Methods And Results: We retrospectively collected data from 79 patients hospitalized with aborted cardiac arrest (resuscitated from a cardiac arrest), ventricular tachycardia (VT), or syncope who underwent a CMR at the Copenhagen University Hospital, Rigshospitalet, Denmark. Besides CMR, the patients were evaluated with an electrocardiogram, echocardiogram (both 100%), coronary angiogram (CAG)/coronary computed tomography scan (CT-CAG) (81%), exercise stress test (47%), late potentials (54%), electrophysiological study (44%), pharmacological provocation (44%), and/or myocardial biopsy (16%). Family screening was indicated for 53 probands (67%) prior to CMR. After full workup, only 43 cases (54%) warranted evaluation of relatives (19% decrease, P = 0.034). The full evaluation changed whether family screening was indicated in 18 probands (14/18 moved to no indication for family screening). In the 18 where recommendations on family screening changed, CMR findings were the major driver for re-classification in 17 cases.
Conclusion: Cardiac magnetic resonance imaging re-defines the cardiac diagnoses in a significant proportion of cases and reduces the number of patients in whom family screening is warranted. Cardiac magnetic resonance imaging is highly relevant for optimal care and resource allocation when an inherited heart disease is the presumed cause of life-threatening arrhythmias.
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http://dx.doi.org/10.1093/europace/euv446 | DOI Listing |
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Department of Public Health, College of Life Sciences, Brigham Young University, 2063 Life Sciences Building, Provo, UT, 84602, USA.
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Artificial Intelligence in Medical Sciences Research Center, Smart University of Medical Sciences, Tehran, Iran.
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