Mortality prediction using a modified Seattle Heart Failure Model may improve patient selection for ventricular tachycardia ablation

BackgroundCatheter ablation is frequently used as a palliative option to reduce shock burden in patients with ventricular tachycardia (VT). A risk prediction tool that accurately predicts short-term survival could improve patient selection for VT ablation.ObjectiveThe objective of the study is to assess utility of the Seattle Heart Failure Model (SHFM) to predict 6-month mortality in patients undergoing VT ablation.MethodsData on patients who underwent VT ablation at 2 tertiary institutions were retrospectively compiled. The SHFM score at the time of ablation, including 2 added VT variables, was used to predict 6-month mortality. The predicted number of deaths was compared to the observed number to assess model calibration. Model discrimination of those who died within 6 months was assessed by both K- and C-statistics.ResultsMean age of the 243 patients was 63 ± 12 years; 89% were male. Mean SHFM score for the cohort was 1.3 ± 1.3. The Kaplan-Meier probability of death within 6 months was 14% (34 patients). The number of deaths estimated by the SHFM at 6 months was 31 (13%) giving a predicted to observed ratio of 0.91 (95% CI 0.64-1.30). The K-statistic for 6-month mortality predictions was 0.77 (95% CI 0.73-0.81), whereas the C-statistic was 0.84 (95% CI 0.78-0.92). Patients with an SHFM score ≥4.0 had an estimated positive predictive value of 80% (95% CI 28%-99%) for dying within 6 months of VT ablation.ConclusionThe SHFM was well calibrated to a sample of patients who underwent VT ablation and provided good discrimination of short-term deaths. This model could be useful as a prognostic tool to improve patient selection for VT ablation.