Accuracy of combined fetal lung volume and pulmonary artery doppler in predicting respiratory distress syndrome after elective cesarean section in diabetic pregnancies.

BACKGROUND/AIM: Neonatal respiratory distress syndrome (RDS) remains a significant cause of morbidity, particularly in infants of diabetic mothers. This study aimed to evaluate the predictive accuracy of non-invasive prenatal ultrasound parameters-Fetal Lung Volume (FLV) and Pulmonary Artery Resistance Index (PA-RI)-for anticipating RDS in this high-risk population.

PATIENTS AND METHODS: This prospective cohort study was conducted at Ain Shams University Maternity Hospital over 18 months. 123 pregnant women with Diabetes scheduled for elective cesarean delivery were enrolled. Within 72 h of pre-delivery, FLV was measured by 3D ultrasonography with VOCAL analysis, and PA-RI was assessed by pulsed-wave Doppler. Neonatal RDS was diagnosed by a blinded pediatrician according to the Vermont Oxford Network criteria. Statistical analysis included ROC curves to determine optimal cut-offs and predictive values.

RESULTS: The incidence of RDS was 13.0% (n = 16). Affected neonates had significantly lower median FLV (29.8 vs. 38.2 cm³, p < 0.001) and higher median PA-RI (0.88 vs. 0.68, p < 0.001). ROC analysis revealed that both parameters were excellent predictors. FLV ≤ 33.5 cm³ showed 93.8% Sensitivity, 87.9% Specificity, 53.6% Positive Predictive Value, and 99.0% Negative Predictive Value (AUC 0.941). PA-RI > 0.75 demonstrated 100% Sensitivity, 90.7% Specificity, 64.0% Positive Predictive Value, and 100% Negative Predictive Value (AUC 0.963). The combined model achieved the highest accuracy (AUC 0.981). Both parameters showed strong correlations with RDS severity (FLV: P = -0.80; PA-RI: P = + 0.77) and NICU stay duration (FLV: P = -0.77; PA-RI: P = + 0.75).

CONCLUSION: FLV and PA-RI are highly accurate, non-invasive tools for predicting neonatal RDS in Diabetic pregnancies. PA-RI, with its perfect Sensitivity and NPV in our cohort, is particularly effective for ruling out the condition, enabling improved perinatal risk stratification and management.