Critical Evaluation of various Sonologic Parameters of Early Foetal Growth Discrepancies in Predicting Adverse Pregnancy Outcomes

Abstract

Introduction: It is well established that adverse perinatal outcomes such as Small for Gestational Age (SGA), preterm delivery, and pre-eclampsia are associated with higher incidence of neonatal complications and death. Evidence suggests that these adverse outcomes may have their origins dating back to early pregnancy growth discrepancies. Aim: To establish an association between early fetal growth discrepancies and occurrence of adverse obstetric outcomes such as pre- clampsia and SGA. Materials and Methods: This is a prospective observational study done in the Department of Obstetrics and Gynaecology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India, between Jan 2015 to May 2016 involving 314 pregnant women, using Crown Rump Length (CRL) measurements at the time of early anomaly (11-14 week scan). Pregnancies with congenital and chromosomal defects, multifetal gestation and non viable foetuses were excluded from the study. The biometric parameters mainly Biparietal Diameter (BPD), Head Circumference (HC), Abdominal Circumference (AC), Femur Length (FL), and Estimated Foetal Weight (EFW) at the time of targeted organ scan (between 18 to 20 weeks) were recorded and reverse calculations were done to convert these parameters to corresponding GA based on published regression formulae. The GA at the time of targeted scan was also calculated based upon the first trimester CRL values. The growth discrepancy was calculated by deducting CRL based GA from biometrically estimated GA for each individual growth parameters. Fisher’s-exact test was used to compare the means of biometric lags in SGA vs. Appropriate for Gestational Age (AGA) fetuses and also in Pre-eclampsia vs. normotensive groups. For each biometric parameter, the best cut-off for discrepancy value was determined using Receiver Operator Characteristic (ROC) analysis along with their diagnostic ability to predict occurrence of SGA in terms of sensitivity, specificity, positive and negative likelihood ratio with their 95% confidence intervals. The Area Under Curve (AUC) and z-test statistics were taken into account to decide the best parameter to predict adverse outcome. A p-value of <0.05 was considered statistically significant.Results: Out of 314 women studied, 62 (19.7%) delivered an SGA neonate, and 30 (9.5%) had pre-eclampsia. All biometric parameters of SGA babies showed growth lag compared to AGA babies which was statistically significant (BPD p<0.001, HC p<0.001, AC p<0.001, FL p<0.01, and EFW p<0.001). However, we could not establish similar associations between early growth discrepancies and onset of pre-eclampsia.Conclusion: Models of second trimester growth discrepancies can be used to predict SGA babies. Earlier anticipation of adverse perinatal outcome may add to quality of antenatal care and timely delivery to prevent late stillbirths associated with SGA.