Background: Fetal lung maturity (FLM) is closely associated with neonatal mortality, morbidity, and respiratory diseases such as neonatal respiratory distress syndrome (NRDS). At present, the assessment of FLM largely relies on invasive procedures, while the establishment of a noninvasive ultrasound-based method has important clinical significance.
Objective: To construct and validate a predictive model of FLM based on ultrasound parameters in late pregnancy, exploring a noninvasive approach for risk assessment in fetal lung development.
Methods: A total of 195 pregnant women (gestational age ≥34 weeks) who underwent ultrasound examinations at the Department of Ultrasound, The Fourth Hospital of Shijiazhuang, China, from January to December 2023 were enrolled. Maternal baseline information, ultrasound parameters, and neonatal outcomes were collected. Fetal lung maturity was assessed based on the occurrence of neonatal respiratory distress syndrome (NRDS), diagnosed using standard clinical criteria including symptoms, blood gas analysis, and chest X-ray findings. Propensity score matching (PSM) was performed with gestational age and corticosteroid use as matching conditions. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to identify key predictors of FLM, and a nomogram prediction model was constructed. The model's discrimination and clinical utility were evaluated using 1,000 bootstrap resamples and 10-fold cross-validation.
Results: Among the 195 participants, the incidence of NRDS was 23.07%. Placental maturity, fetal breathing movement scores, and biparietal diameter were significantly higher in the lung-mature group compared with the NRDS group, while the proportion of gestational diabetes mellitus (GDM) was significantly higher in the NRDS group (all p < 0.005). Multivariate logistic regression after LASSO selection showed that GDM, placental maturity (p < 0.05), and biparietal diameter (OR = 0.027, 95% CI: 0.006-0.101, p < 0.001) were independent predictors of FLM. A nomogram incorporating these three predictors achieved an AUC of 0.871, and both bootstrap validation and 10-fold cross-validation showed promising discriminative ability in this sample; however, this performance is preliminary and requires validation in independent cohorts.
Conclusion: The nomogram developed in this study represents a preliminary model for evaluating fetal lung maturity using ultrasound measurements. However, these findings are from a small, single-center, cross-sectional study and require external validation in larger, diverse populations. BPD, gestational diabetes, and placental maturity play critical roles in FLM and warrant enhanced monitoring and management in clinical practice.
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