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Role of Myocardial Fibrosis in Hypertrophic Cardiomyopathy: A Systematic Review and Updated Meta-Analysis of Risk

Marcelo Imbroinise Bittencourt1, Samária Ali Cader1, Denizar Vianna Araújo1

  • 1Hospital Universitário Pedro Ernesto da Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ - Brazil.

Arquivos Brasileiros De Cardiologia
|March 28, 2019
PubMed

Insights

Myocardial fibrosis is a key predictor of sudden death in hypertrophic cardiomyopathy (HCM). This meta-analysis confirms fibrosis and other risk markers (RMs) predict severe arrhythmic outcomes, highlighting the need for improved risk prediction models.

Area of Science:

  • Cardiology
  • Genetics
  • Pathology

Background:

  • Hypertrophic cardiomyopathy (HCM) is a significant cause of sudden death (SD).
  • Myocardial fibrosis is increasingly recognized as a potential correlate of SD in HCM patients.

Purpose of the Study:

  • To conduct a systematic review and meta-analysis of risk markers (RMs) for severe arrhythmic outcomes in HCM.
  • To specifically emphasize the role of myocardial fibrosis as a predictor of SD in HCM.

Main Methods:

  • Systematic review and meta-analysis of studies from MEDLINE, LILACS, and SciELO databases.
  • Inclusion of studies addressing severe arrhythmic outcomes and specific RMs in HCM.
  • Utilized relative risks (RRs) with random models, setting significance at p < 0.05.

Main Results:

  • Twenty-one studies involving 14,901 patients were analyzed.
  • Myocardial fibrosis emerged as the strongest RM for severe arrhythmic outcomes (RR, 3.43).
  • Other significant RMs included family history of SD, severe ventricular hypertrophy, syncope, non-sustained ventricular tachycardia (NSVT), and abnormal blood pressure response to exercise (ABPRE). Left ventricular outflow tract obstruction (LVOTO) was not a significant predictor in this analysis.

Conclusions:

  • Myocardial fibrosis and other identified RMs are confirmed predictors of severe arrhythmic outcomes in HCM.
  • The findings underscore the necessity for developing novel prediction models for managing HCM patients at risk of sudden death.
Abstract

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