Key result
CMR-based risk score predicts ~649% higher MACE risk in high-risk ETLV patients.
Why the study?
Excessive trabeculation of the left ventricle is a controversial entity with inconsistent outcomes, and CMR may help in risk stratification.
Can a CMR-based risk prediction score accurately predict MACE in patients with excessive trabeculation of the left ventricle?
Can a CMR-based risk prediction score accurately predict MACE in patients with excessive trabeculation of the left ventricle?
A novel CMR-based risk score incorporating conventional and advanced parameters effectively stratifies the risk of major adverse cardiovascular events in patients with excessive trabeculation of the left ventricle.
May support ETLV risk stratification by CMR; leaves open prospective validation before clinical use.
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
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Casas et al. (2025) studied this question.
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