Cord blood biomarkers predict neonatal respiratory dysfunction after prenatal smoke exposure: A decision tree model.

BACKGROUND

Prenatal smoke exposure impairs fetal lung development, but the interplay between cotinine, oxidative stress, and early respiratory dysfunction remains unclear. This study aimed to quantify the effects of prenatal smoke exposure on neonatal respiratory function and develop a validated predictive model to identify this dysfunction.

METHODS

This prospective cohort study included term newborns with prenatal tobacco smoke exposure (n = 50) and healthy controls (n = 41). Cord blood cotinine, oxidative stress markers, and tidal breathing parameters assessed at 48 h post-delivery were compared. A decision tree model was developed and rigorously validated for performance, calibration, and temporal stability to predict decreased expiratory flow.

RESULTS

Smoke-exposed newborns exhibited significantly impaired expiratory flow (p < .001), elevated cord cotinine (p < .001), and increased systemic oxidative stress (p < .05). The decision tree model selected a cord blood cotinine level >26.1 ng/mL as the primary predictor, conferring a 94% probability of dysfunction. For those with lower cotinine, a total oxidant status >9.75 μmol/L was a secondary predictor (87.5% probability). The final model achieved 72.5% accuracy and demonstrated good calibration.

CONCLUSION

Prenatal smoke exposure induces quantifiable neonatal respiratory dysfunction mediated by oxidative stress. Cord blood cotinine and total oxidant status are robust biomarkers for risk stratification. Our validated decision tree offers a practical framework for identifying respiratory dysfunction in newborns.