Rapid Fire Abstracts
Jeremy FLORENCE, MD
Cardiologist
Lariboisière hospital, APHP, Paris, France., France
Jeremy FLORENCE, MD
Cardiologist
Lariboisière hospital, APHP, Paris, France., France
Jerome Garot, PhD
Head
ICPS - Massy, France
Solenn Toupin, PhD
Clinical scientist
Siemens Healthineers, France
Theo Pezel, MD, PhD
Cardiologist
Hôpital Lariboisière – APHP, Paris, France, France
The prognostic stratification of hypertrophic cardiomyopathy (HCM) using cardiac magnetic resonance (CMR) is based on the extent of late gadolinium enhancement (LGE).(1) To enhance risk stratification for sudden cardiac death (SCD), the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) have recently added the extent of LGE in the guidelines, setting a threshold at ≥15%LGE of left ventricular mass.(2,3) However, SCD has become an uncommon event in this population, and mortality is now mostly related to other phenotypes, such as atrial fibrillation, stroke, and heart failure.(4) While previous studies have showed the prognostic value of LGE to predict all-cause mortality, the prognostic impact of additional LGE features is not well established.(5) Therefore, we aimed to assess the incremental prognostic value of the LGE granularity including extent, location, and pattern in patients with HCM to predict all-cause death.
Methods:
Between 2008 and 2021, all patients referred for HCM assessment using CMR, without history of coronary artery disease (CAD) or clinical history of myocarditis were prospectively recruited in two French centers. The outcome was all-cause death using the French National Registry of Death. The concept of “LGE granularity” was defined as a comprehensive model combining all the following LGE features with extent (by segment), location (septal or others), and pattern (midwall and/or subepicardial). Using nested Cox proportional hazard models, the additional predictive value of LGE features was assessed by the C-statistic increment, the continuous net reclassification improvement (NRI), the integrative discrimination index (IDI) and the global Chi-2.
Results:
Among the 2,672 included patients (52±7 years, 56% males), 862 (32%) had LGE. After a median (IQR) follow-up of 9 (7–11) years, 447 (17%) patients died. After adjustment for traditional prognosticators in the overall population (N=2,672), the presence of LGE was strongly associated with all-cause death (adjusted hazard ratio (HR) 3.96, 95% CI: 3.26-4.80, p< 0.001). In patients with LGE (n=862), survival curves showed that all parameters defining the “LGE granularity” were associated with a higher risk of all-cause death (all p< 0.001) (Figure 1). A nested Cox model adjusted on traditional prognosticators showed that the “LGE granularity model” including LGE extent ( >3 segments, HR: 4.1 [95% CI: 2.94-5.73]), septal location (HR: 2.5 [95%CI: 1.79-3.48]), and both midwall and subepicardial pattern (HR: 9.89 [95% CI: 4.12-23.74], all p< 0.001) were all independently associated with all-cause death (Table 2). The model of “LGE granularity” showed the best improvement in model discrimination and reclassification above traditional prognosticators (C-statistic improvement: 0.1; NRI=46.8%; IDI=19.5%, Chi-2 global=469, all p< 0.05; LR-test p< 0.001, Figure 2). The prognostic value of LGE remained consistent in different subgroups of clinical interest, such as sex, age and LVEF (all p< 0.001), except for NYHA ≥II status (p=0.225) (Figure 3).
Conclusion:
In a large cohort of HCM patients, the “LGE granularity” model combining the extent, location, and pattern of LGE had an incremental prognostic value over and above traditional prognosticators and LGE extent to predict all-cause death.