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.