Development and validation of a new CMR risk prediction score in excessive trabeculation of the left ventricle

Abstract Background Excessive trabeculation of the left ventricle (ETLV) is a controversial entity with inconsistent outcomes. Cardiovascular magnetic resonance (CMR) may help in risk stratification. Purpose To develop a CMR prediction model of major adverse cardiovascular events (MACE) in ETLV. Methods Retrospective longitudinal international study. A total of 589 patients with ETLV from 17 centres across Europe and North America were recruited, 398 (67%) were assigned to the development cohort and 191 (33%) to the validation cohort. Also, 197 patients with DCM were recruited as a control group. Core-lab CMR analysis was performed, including conventional parameters (LVEF, burden of LGE, etc.) and advanced variables (all chambers strain, hemodynamic forces, etc.). MACE was defined as a composite of heart failure, ventricular arrhythmias, systemic embolisms and all-cause death. The prediction model with the highest Harrell’s C was chosen. Candidate CMR variables were categorized and converted into a risk score. Patients were divided according to terciles of score punctuation. Results Among the development cohort, age was 43.4 (18.2) years and 45% were women. LVEF was 48.0 (14.1) and 12% exhibited LGE (Figure 1). During a median follow-up of 2.8 years (IQR 0.99 – 5.55) years, MACE occurred in 77 (19%) patients. Most CMR variables were associated with MACE in univariate analysis (Figure 1). The best prediction model resulted to be a combination of indexed LV end-diastolic volume (iLVEDV), LVEF, LGE 5% (of total myocardial mass), left atrium global longitudinal strain (LA-GLS) and lateral-septal hemodynamic forces (ls-HDF). The risk score had a Harrell’s C of 0.742 (Figure 2a) and an adequate calibration (slope 1.04). Patients in the intermediate-risk group had a HR 4.32 (2.37 – 7.86) for MACE compared with those at low risk, and patients in the high-risk group had a HR 7.49 (4.34 – 12.92) (Figure 2b). These results were replicated in the validation cohort (Harrell’s C 0.716), that also displayed a good calibration. However, the performance of the model was only modest when applied to a DCM control cohort (Harrell’s C 0.599). Conclusions We developed and validated a CMR-based risk score for precise stratification in patients with excessive trabeculation of the LV. The modest results in a control DCM group suggest a differential phenotype. Our results could be used for individualised management.Baseline CMR variables ROC and Kaplan Meier curves for MACE