Energy loss index reclassified 29% of patients from severe to moderate AS, showing stronger correlation with GLS (r = -0.443, p = 0.0003) than AVA and better myocardial function.
Does energy loss index (ELI) assessment improve correlation with subclinical myocardial dysfunction (GLS) compared to conventional aortic valve area (AVA) in patients with moderate-to-severe aortic stenosis and preserved LVEF?
Energy loss index (ELI) provides a more physiologically reflective assessment of hemodynamic burden in aortic stenosis than AVA, better correlating with subclinical myocardial dysfunction and identifying patients with less severe disease.
Absolute Event Rate: 0% vs 0%
Background: Traditional echocardiographic assessment of aortic stenosis (AS) using aortic valve area (AVA) may overestimate severity due to pressure recovery phenomena, while subclinical myocardial dysfunction remains undetected despite preserved ejection fraction. This study evaluated whether energy loss index (ELI)—which accounts for pressure recovery—demonstrates superior correlation with global longitudinal strain (GLS), a marker of subclinical myocardial dysfunction, compared to conventional AVA-based classification in patients with moderate-to-severe AS and preserved left ventricular ejection fraction (LVEF). Methods: This retrospective single-center study analyzed 149 patients with moderate-to-severe AS (AVA 50% from 2015 to 2019. Among 97 patients with severe AS by AVA (<1.0 cm2), ELI was calculated using the formula ELI = (AVA × Aa)/(Aa − AVA) ÷ BSA, where Aa represents sinotubular junction cross-sectional area. Patients with ELI ≥ 0.6 cm2/m2 were reclassified as moderate AS. Spearman correlation assessed relationships between AVA, ELI, and GLS. Multivariable linear regression models determined independent predictors of myocardial dysfunction, adjusting for age, body surface area, hypertension, LVEF, and mean pressure gradient. Results: ELI reclassified 28 of 97 patients (29%) from severe to moderate AS. Reclassified patients had significantly better myocardial function, with less impaired GLS (−15.0 ± 3.9% vs. −12.1 ± 5.0%, p = 0.013) and higher LVEF (60.1 ± 6.2% vs. 56.5 ± 9.1%, p = 0.017) compared to non-reclassified patients. In the overall cohort, ELI demonstrated stronger correlation with GLS than AVA (r = −0.307, p = 0.0003 vs. r = −0.209, p = 0.0115). Critically, among patients with severe AS by AVA criteria, ELI maintained significant correlation with GLS (r = −0.443, p = 0.0003) while AVA showed no correlation (r = −0.144, p = 0.159). In multivariable analysis, ELI independently predicted GLS (β = 5.847, 95% CI: 2.85–8.84, p = 0.0002; adjusted R2 = 0.289), whereas AVA did not (β = 2.234, 95% CI: −1.08 to 5.55, p = 0.188; adjusted R2 = 0.234). When both parameters were included simultaneously, only ELI remained significant (p = 0.0024). Conclusions: In this retrospective cohort, ELI-based reclassification identified a subgroup of patients with less severe myocardial dysfunction as measured by GLS and LVEF, and ELI demonstrated superior correlation with subclinical myocardial dysfunction compared to AVA. These findings suggest ELI may provide a more physiologically reflective assessment of hemodynamic burden in AS with preserved LVEF. However, the absence of systematic symptom assessment and clinical outcome data represents critical limitations. Prospective studies with standardized symptom evaluation, longitudinal follow-up, and adjudicated clinical endpoints are required to determine whether ELI-based reclassification improves risk stratification and clinical decision-making before this approach can be recommended for routine practice.
Zayed et al. (Fri,) reported a other. Energy loss index reclassified 29% of patients from severe to moderate AS, showing stronger correlation with GLS (r = -0.443, p = 0.0003) than AVA and better myocardial function.