A New Approach for Classifying Fetal Growth Restriction

Area of Science:

• Perinatal Medicine
• Neonatal Health
• Biostatistics

Background:

• Current definition of fetal growth restriction (FGR) relies on small for gestational age (SGA) birthweight (<10th percentile) as a proxy.
• This SGA proxy is problematic as most SGA infants are healthy, leading to misclassification and missed diagnoses of true FGR.
• There is a need for a more accurate method to identify FGR at birth.

Purpose of the Study:

• To develop and validate a novel probabilistic approach for identifying fetal growth restriction at birth.
• To combine multiple imperfect measures of fetal growth into a single classification model.
• To compare the clinical characteristics and outcomes of infants classified by the new model versus the conventional SGA proxy.

Main Methods:

• Latent profile analysis (LPA) was used to classify fetal growth.
• Data included birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia from 26,077 births (2001-2009).
• Clinical characteristics and health outcomes were compared between growth-restricted and non-growth-restricted infants identified by LPA.

Main Results:

• The LPA model identified 345 (1.3%) growth-restricted infants.
• Growth-restricted infants showed significantly higher rates of Apgar score <7, hypoglycemia, NICU admission, perinatal death, and emergency cesarean delivery.
• The model identified at-risk infants who were not small for gestational age, indicating improved detection over the SGA proxy.

Conclusions:

• Latent profile analysis offers a promising strategy for improved classification of fetal growth restriction at birth.
• This probabilistic approach enhances the identification of infants at risk for adverse outcomes.
• Further research using LPA in FGR is warranted.