Risk factor algorithm used to predict frequent premature ventricular contraction-induced cardiomyopathy.

BACKGROUND

Premature ventricular contraction (PVC) QRS duration (QRSd) and high PVCs burden are known as a risk factor of PVC-induced cardiomyopathy (CMP). The aim of this study is to find useful algorithm to predict PVC-induced CMP.

METHODS

180 patients (99 males, 51±14years) with frequent PVCs (>10%/24h), who underwent successful PVC ablation, were studied. Typical PVC-related symptoms were defined as the presence of palpitations or dropped beats during PVC. Group A (n=144) was symptomatic and Group B (n=36) was asymptomatic.

RESULTS

The incidence of CMP was significantly higher in group B (group A=19%, group B=66%, p<0.001). In group A, there were significant differences, between the patients with normal EF and CMP, in terms of sex (p=0.005), daily PVC burden (p=0.012), distribution of PVCs with a LV site (p<0.009), and PVC QRSd (p<0.001). In group B, the PVC QRSd was significantly wider in patients with CMP. Multivariate analysis showed that PVC QRSd (p<0.001), PVC burden (p=0.022), and LV site (p=0.043) were risk factors for CMP.

CONCLUSIONS

Using our scoring algorithm for this patient sample, we are able to predict the development of PVC-induced CMP with 80% sensitivity, 81% specificity, 64% positive predictive value, and 91% negative predictive value.