GENECHOC study: A study designed to identify the genetic variants involved in appropriate shock in primary prevention. Clinical description of the patients

Abstract

Arrhythmic risk stratification for primary prevention in patients with severe cardiomyopathy (CM) remains difficult. We established a large database of patients implanted for primary prevention with the aim to identify genetic modifiers involved in the occurrence of arrhythmic events. We described the clinical characteristics of patients included in the study. Patients were included in 22 French centers over a 9 year-period. Only patients implanted for primary prevention (no previous arrhythmias at the time of implantation in patients who had an EF less than 35%). Patients implanted with a resynchronization therapy were not included in the study. 1079 patients were enrolled (mean age 59 ± 11, 86.3% male). Ischemic CM was found in 77.1% and 20.5% had a non-ischemic CM. The mean EF was 27 ± 7%. The population was well treated with beta-blockers treatment in 89.9% and angiotensin converting enzyme inhibitors in 90.7%. VVI ICD was implanted in 721 patients (67%) and DDD ICD in 357 (33%). After a mean follow-up of 5.5 ± 2.5 years appropriate ICD therapy occurred in 388 (35.9%) patients. Predictive factors for appropriate therapy were male gender (38.2% in male vs. 21.6% in women, P = 9.10 −5 ). There was no significant difference for EF, 27.2 ± 5.3 in patients without ICD therapy vs. 26.8 ± 5 in patients with ICD therapy. The etiology of CM (ischemic vs. non ischemic) didn’t change the rate of appropriate therapy (respectively 34.9% vs. 37.7%, P = 0.4). 61 patients (5.6%) received inappropriate therapies mainly because of supraventricular tachycardia ( n = 24, 39.3%), T wave oversensing ( n = 11, 18%) and lead failure ( n = 14, 22.9%). Our population is similar in term of arrhythmic risk and clinical presentation to the usual population implanted for primary prevention. As for the first time this population is homogenous in term of geographic origin, it will allow using a GWAS analysis to identify genetic modifiers involved in SCD.