Left Atrial Function Using Cardiovascular Magnetic Resonance Imaging Independently Predicts Life-Threatening Arrhythmias in Patients Referred to Receive a Primary Prevention Implantable Cardioverter Defibrillator

Left atrial volume and function measured by cardiac magnetic resonance imaging as predictors of shocks and mortality in patients with implantable cardioverter-defibrillators

Left atrial (LA) volume and function (LA ejection fraction, LAEF) have demonstrated prognostic value in various cardiovascular diseases. We investigated the incremental value of LA volume and LAEF as measured by cardiovascular magnetic resonance imaging (CMR) for prediction of appropriate implantable cardioverter defibrillator (ICD) shock or all-cause mortality, in patients with ICD. We conducted a retrospective, multi-centre observational cohort study of patients who underwent CMR prior to primary or secondary prevention ICD implantation. A single, blinded reader measured maximum LA volume index (maxLAVi), minimum LA volume index (minLAVi), and LAEF. The primary outcome was a composite of independently adjudicated appropriate ICD shock or all-cause death. A total of 392 patients were enrolled. During a median follow-up time of 61 months, 140 (35.7%) experienced an appropriate ICD shock or died. Higher maxLAVi and minLAVi, and lower LAEF were associated with greater risk of appropriate ICD shock or death in univariate analysis. However, in multivariable analysis, LAEF (HR 0.92 per 10% higher, 95% CI 0.81-1.04, p = 0.17) and maxLAVi (HR 1.02 per 10 ml/m² higher, 95% CI 0.93-1.12, p = 0.72) were not independent predictors of the primary outcome. In conclusion, LA volume and function measured by CMR were univariate but not independent predictors of appropriate ICD shocks or mortality. These findings do not support the routine assessment of LA volume and function to refine risk stratification to guide ICD implant. Larger studies with longer follow-up are required to further delineate the clinical implications of LA size and function.

Baseline and Dynamic Risk Predictors of Appropriate Implantable Cardioverter Defibrillator Therapy

Background Current approaches fail to separate patients at high versus low risk for ventricular arrhythmias owing to overreliance on a snapshot left ventricular ejection fraction measure. We used statistical machine learning to identify important cardiac imaging and time-varying risk predictors. Methods and Results Three hundred eighty-two cardiomyopathy patients (left ventricular ejection fraction ≤35%) underwent cardiac magnetic resonance before primary prevention implantable cardioverter defibrillator insertion. The primary end point was appropriate implantable cardioverter defibrillator discharge or sudden death. Patient characteristics; serum biomarkers of inflammation, neurohormonal status, and injury; and cardiac magnetic resonance-measured left ventricle and left atrial indices and myocardial scar burden were assessed at baseline. Time-varying covariates comprised interval heart failure hospitalizations and left ventricular ejection fractions. A random forest statistical method for survival, longitudinal, and multivariable outcomes incorporating baseline and time-varying variables was compared with (1) Seattle Heart Failure model scores and (2) random forest survival and Cox regression models incorporating baseline characteristics with and without imaging variables. Age averaged 57±13 years with 28% women, 66% white, 51% ischemic, and follow-up time of 5.9±2.3 years. The primary end point (n=75) occurred at 3.3±2.4 years. Random forest statistical method for survival, longitudinal, and multivariable outcomes with baseline and time-varying predictors had the highest area under the receiver operating curve, median 0.88 (95% CI, 0.75-0.96). Top predictors comprised heart failure hospitalization, left ventricle scar, left ventricle and left atrial volumes, left atrial function, and interleukin-6 level; heart failure accounted for 67% of the variation explained by the prediction, imaging 27%, and interleukin-6 2%. Serial left ventricular ejection fraction was not a significant predictor. Conclusions Hospitalization for heart failure and baseline cardiac metrics substantially improve ventricular arrhythmic risk prediction.