The impact of fragmented QRS on clinical findings and outcomes in children with dilated cardiomyopathy with or without left ventricular non-compaction.

Objective: The aim of this study is to investigate the frequency of fragmented QRS and its associations with clinical findings and prognosis in children diagnosed with dilated cardiomyopathy with or without left ventricular non-compaction.

Methods: This retrospective study was conducted between 2010 and 2020. Patients with dilated cardiomyopathy were classified into two groups according to the presence of left ventricular non-compaction: Dilated cardiomyopathy with left ventricular non-compaction and dilated cardiomyopathy without left ventricular non-compaction. Patients were also divided into two groups according to the presence of fragmented QRS (fragmented QRS group and non-fragmented QRS group).

Results: Twenty-three of 44 patients (52.3%) were male. Among left ventricular non-compaction patients, the fragmented QRS group had more complex ventricular arrhythmias (p = 0.003). Patients with fragmented QRS had a significantly higher rate of major adverse cardiac events and/or cardiac death in both cardiomyopathy groups (p = 0.003 and p = 0.005). However, the rate of major adverse cardiac events and/or cardiac death was similar between dilated cardiomyopathy patients with and without left ventricular non-compaction. Multivariate logistic regression analysis showed that the presence of fragmented QRS strongly predicts major adverse cardiac events and/or cardiac death (odds ratio, 31.186; 95% confidence interval, 2.347-414.307). Although the survival rates between cardiomyopathy groups were similar, patients with fragmented QRS had a markedly lower survival rate during the follow-up period, as mean of 15 months (p = 0.001).

Conclusion: Our study showed that the presence of fragmented QRS may be an important ECG sign predicting an major adverse cardiac event and/or cardiac death in patients with dilated cardiomyopathy. We believe that recognising fragmented QRS could be valuable in forecasting patient prognosis and identifying high-risk patients who require additional support.