Objective: To evaluate the impact of late 3rd trimester fetal growth cessation on anatomical birth characteristic predictions used in classifying SGA neonates.

Methods: A prospective longitudinal study was performed in 119 pregnancies with normal neonatal growth outcomes. Seven biometric parameters were measured at 3-4 weeks intervals using 3D ultrasonography. Rossavik size models were determined to predict birth characteristics at different ages. Percent Differences (% Diff) were calculated from predicted and measured birth characteristics. Growth Cessation Ages (GCA) were identified when no systematic change in % Diff values occurred after specified prediction ages. Systematic and random prediction errors were compared using different assumptions about the GCA. Predicted and measured size parameters were used to determine six new Growth Potential Realization Index (GPRI) reference ranges. Five were used to sub-classify 34 SGA neonates (weight < 10th percentile) based on the number of abnormal GPRI values.

Results: Growth cessation ages were 38 weeks for HC, AC, mid-thigh circumference, estimated weight and mid-arm circumference. Crown-heel length GCA was 38.5 weeks. At GCA, birth characteristics had prediction errors that varied from 0.08 ± 3.4% to 15.7 ± 9.1% and zero % Diff slopes after 38 weeks. Assuming growth to delivery gave increased systematic and random prediction errors as well as positive % Diff slopes after 38 weeks, MA. Seventeen of the SGA neonates had 0 or 1 abnormal GPRI values [Subgroup 1] and 17 others had 2 or more abnormal values [Subgroup 2]. In Subgroup 1, 4/85 (4.7%) of GPRI's were abnormal while in Subgroup 2, 43/85 (50.6%) were abnormal. Use of only one type of GPRI for SGA subclassification resulted in substantial false negative and some false positive rates when compared to subclassification based on all five GPRI values.

Conclusions: Growth cessation occurred at approximately 38 weeks for all six birth characteristics studied. SGA neonates can be separated into normal and growth restricted subgroups based on the frequency of abnormal GPRI values (GPRI Profile Classification).

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537184PMC
http://dx.doi.org/10.3109/14767058.2014.934219DOI Listing

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