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Heart failure (HF) admission is a dominant contributor to morbidity and healthcare costs in dilated cardiomyopathy (DCM). Mid-wall striae (MWS) fibrosis by late gadolinium enhancement (LGE) imaging has been associated with elevated arrhythmia risk. However, its capacity to predict HF-specific outcomes is poorly defined. We investigated its role to predict HF admission and relevant secondary outcomes in a large cohort of DCM patients. 719 patients referred for LGE MRI assessment of DCM were enrolled and followed for clinical events. Standardized image analyses and interpretations were conducted inclusive of coding the presence and patterns of fibrosis observed by LGE imaging. The primary clinical outcome was hospital admission for decompensated HF. Secondary heart failure and arrhythmic composite endpoints were also studied. Median age was 57 (IQR 47-65) years and median LVEF 40% (IQR 29-47%). Any fibrosis was observed in 228 patients (32%) with MWS fibrosis pattern present in 178 (25%). At a median follow up of 1044 days, 104 (15%) patients experienced the primary outcome, and 127 (18%) the secondary outcome. MWS was associated with a 2.14-fold risk of the primary outcome, 2.15-fold risk of the secondary HF outcome, and 2.23-fold risk of the secondary arrhythmic outcome. Multivariable analysis adjusting for all relevant covariates, inclusive of LVEF, showed patients with MWS fibrosis to experience a 1.65-fold increased risk (95% CI 1.11-2.47) of HF admission and 1-year event rate of 12% versus 7% without this phenotypic marker. Similar findings were observed for the secondary outcomes. Patients with LVEF > 35% plus MWS fibrosis experienced similar event rates to those with LVEF ≤ 35%. MWS fibrosis is a powerful and independent predictor of clinical outcomes in patients with DCM, identifying patients with LVEF > 35% who experience similar event rates to those with LVEF below this conventionally employed high-risk phenotype threshold., (© 2022. The Author(s).)

Background: There is increasing evidence that right ventricular ejection fraction (RVEF) may provide incremental value to left ventricular (LV) ejection fraction for the prediction of major adverse cardiovascular events. To date, generalizable utility for RVEF quantification in patients with cardiovascular disease has not been established. Using a large prospective clinical outcomes registry, we investigated the prognostic value of RVEF for the prediction of major adverse cardiovascular events- and heart failure-related outcomes., Methods: Seven thousand one hundred thirty-one consecutive patients with known or suspected cardiovascular disease undergoing cardiovascular magnetic resonance imaging were prospectively enrolled. Multichamber volumetric quantification was performed by standardized operational procedures. Patients were followed for the primary composite outcome of all-cause death, survived cardiac arrest, admission for heart failure, need for transplantation or LV assist device, acute coronary syndrome, need for revascularization, stroke, or transient ischemic attack. A secondary, heart failure focused outcome of heart failure admission, need for transplantation/LV assist device or death was also studied., Results: Mean age was 54±15 years. The mean LV ejection fraction was 55±14% (range 6%-90%) with a mean RVEF of 54±10% (range 9%-87%). At a median follow-up of 908 days, 870 (12%) patients experienced the primary composite outcome and 524 (7%) the secondary outcome. Each 10% drop in RVEF was associated with a 1.3-fold increased risk of the primary outcome ( P <0.001) and 1.5-fold increased risk of the secondary outcome ( P <0.001). RVEF was an independent predictor following comprehensive covariate adjustment, inclusive of LV ejection fraction. Patients with an RVEF<40% experienced a 3.1-fold risk of the primary outcome ( P <0.001) with a 1-year cumulative event rate of 22% versus 7% above this cutoff., Conclusions: RVEF is a powerful and independent predictor of major adverse cardiac events with broad generalizability across patients with known or suspected cardiovascular disease. These findings support migration towards biventricular phenotyping for the classification of risk in clinical practice. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04367220.