Improved prediction of electrical storm in patients with prior myocardial infarction and implantable cardioverter defibrillator.

Int J Cardiol

Cardiology Department, Bellvitge University Hospital, Hospitalet de Llobregat, Barcelona, Spain; BIOHEART-Cardiovascular diseases group; Cardiovascular, Respiratory and Systemic Diseases and cellular aging Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain. Electronic address:

Published: May 2022

Aims: To evaluate predictors of electrical storm (ES), including chronic total occlusion in an infarct-related coronary artery (infarct-related artery CTO, IRACTO), in a cohort of patients with prior myocardial infarction (MI) and implantable cardioverter-defibrillators (ICD).

Methods: Multicenter observational cohort study including 643 consecutive patients with prior MI and a first ICD implanted between 2005 and 2018 at three tertiary hospitals. All the patients included in the study had undergone a diagnostic coronary angiography before ICD implantation. The variable prior ventricular arrhythmias (VA+) was positive in patients with secondary prevention ICDs and in those with at least one appropriate ICD therapy after primary prevention implantation.

Results: During a median follow-up of 42 months 59 patients (9%) suffered ES. The presence of at least one IRACTO not revascularized (IRACTO-NR) was associated with a significantly higher cumulative incidence of ES (14.5% vs 4.8%, p < 0.001). IRACTO-NR maintained a significant association with ES after adjustment for potential confounders (HR 2.3, p = 0.005) and was an independent predictor of ES together with VA+ and LVEF. The best cut-off of LVEF to predict ES was ≤38%. A risk-prediction model based on IRACTO-NR, VA+ and LVEF≤38% identified three categories of ES risk (low, intermediate and high), with progressively increasing cumulative incidence of ES (2.2%, 9% and 20%).

Conclusion: In a cohort of patients with prior MI and ICD, IRACTO-NR is an independent predictor of ES. A new risk-prediction model allowed the identification of three categories of risk, with potentially important clinical implications.

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Source
http://dx.doi.org/10.1016/j.ijcard.2022.02.016DOI Listing

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