Acoustic Cardiography (ACG) for Left Ventricular Ejection Time (LVET) Monitoring in Preeclampsia Risk Prediction

Abstract

Background

Preeclampsia (PE), a leading cause of maternal morbidity, lacks reliable early biomarkers. This study evaluates acoustic cardiography (ACG) for noninvasive left ventricular ejection time (LVET) monitoring and its predictive value in PE.

Methods

In an observational case-control study, 59 pregnant women (28 controls, 31 PE cases) underwent synchronized ECG-phonocardiogram (PCG) monitoring using AI-driven devices. LVET, Q2S2Max, and hemodynamic parameters were analyzed.

Hypothesis

ACG predict PE risk via LVET monitoring.

Results

Significantly prolonged LVET in the PE group (320.28 ± 26.79 ms vs. 301.32 ± 35.42 ms, p = 0.026), correlating with increased cardiac afterload. ROC analysis revealed moderate diagnostic efficacy for LVET alone (AUC = 0.658, sensitivity 72.4%, specificity 57.1%). Combining LVET with hypertension history enhanced performance (AUC = 0.776, specificity 77.8%), reducing false positives. Elevated Q2S2Max in PE (426.10 ± 29.46 vs. 403.96 ± 33.28, p = 0.010) indicated vascular stiffness, suggesting early vascular-cardiac coupling dysfunction.

Conclusions

ACG-derived parameters, integrated with clinical risk factors, demonstrated cost-effective, dynamic monitoring potential for early PE detection, particularly in resource-limited settings. While limited by sample size and single-center design, this study highlights ACG as a promising tool for cardiovascular risk stratification in pregnancy, warranting further validation in larger cohorts.