The number of conduction channels within the border zone independently predicted arrhythmic events in non-ischemic dilated cardiomyopathy (sHR 1.25; 95% CI 1.11-1.42; p<0.001).
Observational (n=925)
Yes
Does an integrated risk stratification algorithm based on LGE, Cbz, and high-risk genotype improve prediction of arrhythmic events compared to LVEF in patients with non-ischemic dilated cardiomyopathy?
Integrating cardiac magnetic resonance findings (LGE and conduction channels) with high-risk genotype significantly improves arrhythmic risk stratification in non-ischemic dilated cardiomyopathy compared to LVEF alone.
Effect estimate: sHR 1.25 (95% CI 1.11-1.42)
p-value: p=<0.001
Abstract Background and objective Late gadolinium enhancement (LGE) by cardiac magnetic resonance (CMR) and certain genetic variants (1,2) have been identified as risk factors for predicting arrhythmic events in patients with non-ischemic dilated cardiomyopathy (DCM). The detection of channels within the border zone (Cbz) may provide a more detailed characterization of fibrosis (3). The aim was to evaluate the prognostic value of LGE, Cbz, and genotype for predicting arrhythmic events in DCM. Methods Observational study of consecutive DCM patients from 22 European centers who underwent genetic testing and cardiac magnetic resonance (2003-2023). The first available CMR was centrally analysed, and in the presence of LGE, Cbz were quantified using a dedicated software (signal intensity 40–60% for border zone). The composite arrhythmic endpoint (AE) included sudden cardiac death, resuscitated cardiac arrest, sustained ventricular arrhythmia, and/or appropriate implantable cardioverter-defibrillator (ICD) therapy. High-risk genotype (HRG) included FLNC, LMNA, DSP, RBM20, TMEM43, PLN, PKP2, DSC2, DSG2. Results A total of 925 patients were included (64.6% male, mean age 54.5 43.7-63.9 years, mean left ventricular ejection fraction LVEF 37.6% 26.9-44.8) with a median follow-up of 5.4 years (3.3–7.7). A positive genotype was identified in 327 patients (35.4%), and high-risk genetics (HRG) in 119 (12.9%). LGE was present in 225 patients (24.3%). The AE occurred in 95 individuals (10.3%). In multivariable competing-risk analysis, the number of Cbz was an independent predictor of the arrhythmic endpoint (sHR 1.25, 95% CI 1.11–1.42; p0.001), adjusted for LVEF and LGE extent. In patients with LGE, a threshold of ≥4 Cbz identified a high-risk subgroup (annual event rate of 7.4% vs 4.3%). High-risk genotypes were associated with significantly increased arrhythmic risk only in the LGE-negative subgroup (log-rank p 0.001). A stepwise risk stratification algorithm (Figure1) in five categories integrating LGE, Cbz burden, and HRG outperformed LVEF-based classification (C-index 0.71 vs. 0.55), showing a progressive increase in arrhythmic risk across five categories (log-rank p0.001, Figure2). Conclusion Conduction channels and HRG provide independent and additive value for arrhythmic risk stratification in DCM. A novel algorithm integrating LGE, Cbz, and genotype improves arrhythmic risk stratification.
López et al. (Sun,) conducted a observational in non-ischemic dilated cardiomyopathy (DCM) (n=925). Conduction channels within the border zone (Cbz) and high-risk genotype was evaluated on Composite arrhythmic endpoint (sudden cardiac death, resuscitated cardiac arrest, sustained ventricular arrhythmia, and/or appropriate ICD therapy) (sHR 1.25, 95% CI 1.11-1.42, p=<0.001). The number of conduction channels within the border zone independently predicted arrhythmic events in non-ischemic dilated cardiomyopathy (sHR 1.25; 95% CI 1.11-1.42; p<0.001).