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Role of cardiac magnetic resonance in stratifying arrhythmogenic risk in mitral valve prolapse patients: a systematic review and meta-analysis. | LitMetric

AI Article Synopsis

  • The study systematically reviewed and meta-analyzed existing research to assess how cardiac magnetic resonance (CMR) characteristics can predict arrhythmic risks in patients with mitral valve prolapse (MVP).
  • LGE was found to have a strong and significant correlation with complex ventricular arrhythmias (co-VAs), while other CMR features like mitral regurgitation and prolapse distance did not show significant effects.
  • The findings suggest that LGE is crucial for predicting arrhythmia risk in MVP patients, with mitral annular disjunction (MAD) possibly serving as an additional factor for assessment.

Article Abstract

Objectives: To perform a systematic review and meta-analysis of studies investigating the diagnostic value of cardiac magnetic resonance (CMR) features for arrhythmic risk stratification in mitral valve prolapse (MVP) patients.

Materials And Methods: EMBASE, PubMed/MEDLINE, and CENTRAL were searched for studies reporting MVP patients who underwent CMR with assessment of: left ventricular (LV) size and function, mitral regurgitation (MR), prolapse distance, mitral annular disjunction (MAD), curling, late gadolinium enhancement (LGE), and T1 mapping, and reported the association with arrhythmia. The primary endpoint was complex ventricular arrhythmias (co-VAs) as defined by any non-sustained ventricular tachycardia, sustained ventricular tachycardia, ventricular fibrillation, or aborted sudden cardiac death. Meta-analysis was performed when at least three studies investigated a CMR feature. PROSPERO registration number: CRD42023374185.

Results: The meta-analysis included 11 studies with 1278 patients. MR severity, leaflet length/thickness, curling, MAD distance, and mapping techniques were not meta-analyzed as reported in < 3 studies. LV end-diastolic volume index, LV ejection fraction, and prolapse distance showed small non-significant effect sizes. LGE showed a strong and significant association with co-VA with a LogORs of 2.12 (95% confidence interval (CI): [1.00, 3.23]), for MAD the log odds-ratio was 0.95 (95% CI: [0.30, 1.60]). The predictive accuracy of LGE was substantial, with a hierarchical summary ROC AUC of 0.83 (95% CI: [0.69, 0.91]) and sensitivity and specificity rates of 0.70 (95% CI: [0.41, 0.89]) and 0.80 (95% CI: [0.67, 0.89]), respectively.

Conclusions: Our study highlights the role of LGE as the key CMR feature for arrhythmia risk stratification in MVP patients. MAD might complement arrhythmic risk stratification.

Clinical Relevance Statement: LGE is a key factor for arrhythmogenic risk in MVP patients, with additional contribution from MAD. Combining MRI findings with clinical characteristics is critical for evaluating and accurately stratifying arrhythmogenic risk in MVP patients.

Key Points: MVP affects 2-3% of the population, with some facing increased risk for arrhythmia. LGE can assess arrhythmia risk, and MAD may further stratify patients. CMR is critical for MVP arrhythmia risk stratification, making it essential in a comprehensive evaluation.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11519141PMC
http://dx.doi.org/10.1007/s00330-024-10815-3DOI Listing

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