Abstract

Aortic stenosis (AS) and aortic regurgitation (AR) are common across all age groups, yet their co-occurrence in mixed aortic valve disease (MAVD) remains poorly understood, particularly in terms of its impact on left ventricular (LV) performance and clinical assessment. Although patients with congenital aortic valve disease may remain asymptomatic, the risk of irreversible myocardial fibrosis, increased LV wall stress, and sudden death in untreated cases underscores the need for earlier intervention. While treatment guidelines exist for mild and severe cases, the optimal approach for moderate aortic valve disease (modAS, modAR) remains unclear. To address this, we developed a novel noninvasive parameter, LV efficiency, using a mathematical model to evaluate LV performance. The model was first validated in silico and in vivo using synthetic patient data (N = 520) and 25 pediatric patients (9 healthy, 8 modAS, 8 modAR). We then extended the model to MAVD by simulating 46,200 unique combinations of AS and AR severity, stroke volume (50–80 mL), heart rate (60–90 bpm), and systolic pressure (120–140 mmHg). LV efficiency showed a strong nonlinear power-law relationship with stroke work (R2 = 0.813), with healthy subjects maintaining efficiency above 90% (synthetic: 90.74%, in vivo: 92.22%). ModAS cases showed moderate reduction (synthetic: 78.15%, in vivo: 76.29%, p<0.05), while modAR had the lowest values (synthetic: 57.86%, in vivo: 65.81%, p<0.05). Severe MAVD dropped below 20%, and moderate MAVD spanned 60–35%, overlapping with simulated severe AS. These results suggest that LV efficiency may offer a robust tool for monitoring disease severity and guiding intervention, even at the moderate stage. By capturing the combined hemodynamic burden of AS and AR, this parameter has the potential to support earlier risk stratification, optimize clinical decision-making, and improve outcomes across the spectrum of aortic valve disease.