A nomogram to predict large-for-gestational-age in term newborns: A retrospective single-center study

Area of Science:

• Obstetrics and Gynecology
• Neonatal Medicine
• Medical Statistics

Background:

• Large-for-gestational-age (LGA) newborns pose risks to both mother and infant.
• Accurate prediction of LGA is crucial for timely intervention and improved perinatal outcomes.
• Existing prediction methods may lack precision for full-term infants.

Purpose of the Study:

• To develop and validate a predictive nomogram for large-for-gestational-age (LGA) in full-term newborns (37-41 weeks' gestation).
• To identify independent risk factors associated with LGA in this population.
• To assess the nomogram's predictive performance using receiver operating characteristic (ROC) curves.

Main Methods:

• Retrospective single-center study of 1481 full-term deliveries.
• Random assignment of participants into training (n=1017) and validation (n=464) sets.
• Logistic regression analysis to identify independent predictors and construct a nomogram.

Main Results:

• Seven factors were independently associated with LGA: gestational age, gestational weight gain, symphysis-fundal height, fetal abdominal circumference, triglycerides, gestational diabetes mellitus, and low pre-pregnancy BMI.
• The developed nomogram demonstrated favorable predictive performance.
• Areas under the ROC curves were 0.846 in the training set and 0.802 in the validation set.

Conclusions:

• A nomogram incorporating seven key factors can effectively predict LGA in full-term newborns.
• The nomogram shows good discriminative ability in both training and validation cohorts.
• This tool can aid clinicians in identifying high-risk pregnancies for LGA, facilitating targeted management.