Cardiac magnetic resonance imaging in patients referred for premature ventricular contractions: identifying patients most likely to benefit - Report - MDSpire
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Cardiac magnetic resonance imaging in patients referred for premature ventricular contractions: identifying patients most likely to benefit
Clinical Report: Evaluating the Role of Cardiac Magnetic Resonance Imaging in PVCs
Overview
This study assesses the effectiveness of cardiac magnetic resonance (CMR) imaging in detecting structural abnormalities in patients with premature ventricular contractions (PVCs). CMR identified structural abnormalities in 46% of cases, with specific predictive factors linked to these findings.
Background
Premature ventricular contractions (PVCs) are common arrhythmias that can indicate underlying structural heart disease (SHD) in some patients. Detecting SHD is crucial to mitigate risks such as malignant ventricular arrhythmias and sudden cardiac death. Current guidelines recommend initial assessments including electrocardiograms and echocardiography, but these may not fully evaluate certain cardiac structures.
Data Highlights
Finding
Percentage
Nonischemic fibrosis
26.5%
Ischemic fibrosis
9%
Mixed fibrosis
2%
Cardiomyopathies
2%
Key Findings
CMR revealed structural abnormalities in 46% of patients referred for PVCs.
Predictive factors for structural abnormalities included age, male sex, diabetes, smoking, known cardiomyopathy, and pleomorphic PVCs.
Young, nondiabetic patients with normal echocardiography and monomorphic PVCs that decreased with effort had normal CMR findings.
Late gadolinium enhancement (LGE) sequences in CMR can detect focal myocardial fibrosis.
Clinical Implications
The findings suggest that CMR should be considered in the evaluation of PVCs, particularly in patients with identified predictive factors. Understanding which patients are likely to benefit from CMR can optimize resource use and improve patient outcomes.
Conclusion
CMR is a valuable tool in the assessment of PVCs, revealing structural abnormalities in nearly half of the cases studied. Identifying predictive factors can help guide the use of CMR in clinical practice.
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