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.