Nomogram integrating fetal pulmonary artery AT/ET ratio and obstetric factors for prenatal prediction of neonatal respiratory distress syndrome

To investigate the clinical value of the fetal main pulmonary artery Doppler–derived systolic acceleration time/ejection time (AT/ET) ratio for prenatal prediction of neonatal respiratory distress syndrome (NRDS), and to construct a predictive model integrating hemodynamic and clinical parameters. This single-center retrospective study enrolled pregnant women hospitalized for threatened or confirmed preterm labor between January 2024 and March 2025. Based on neonatal outcomes, participants were classified into NRDS and non-NRDS groups. Fetal pulmonary artery Doppler ultrasound was used to measure AT/ET ratios at multiple anatomical segments. Logistic regression determined independent risk factors, and a nomogram was developed accordingly. Model validation was conducted using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). 294 cases were analyzed. The AT/ET ratio at the mid-segment of the main pulmonary artery was significantly lower in fetuses whose neonates developed NRDS (P < 0.001). Multivariate analysis demonstrated that gestational age at Doppler examination and AT/ET ratio were independent protective factors, whereas antenatal glucocorticoid therapy was associated with increased NRDS risk. However, the latter finding likely reflects confounding by indication, as corticosteroids are preferentially administered to pregnancies at highest perceived risk of preterm delivery and subsequent NRDS, and should not be interpreted causally. The nomogram demonstrated excellent discrimination (bootstrap-corrected AUC = 0.969) and good calibration, with a high net clinical benefit across a wide threshold range. To our knowledge, this is the first study to integrate the fetal main pulmonary artery AT/ET ratio with obstetric variables for prenatal prediction of NRDS, offering a novel, noninvasive, multimodal approach for assessing fetal lung maturity. The resulting prediction model exhibits high accuracy and potential utility for individualized perinatal risk stratification.