EP08.49: Comparative assessment of antenatal growth charts in identifying small‐for‐gestational‐age fetuses in Indian population
Year: 2024
Type: conference-abstract
Abstract: To assess the performance in identifying small for gestational age fetuses using three antenatal growth charts (GC) i.e. FMF, MEDISCAN and HADLOCK GCs. The study included 50 patients. The AC centiles used in the dataset were obtained from the converter provided on FMF website, Mediscan from Sonocare software and Hadlock v for their respective GCs. Inclusion criteria were low risk, singleton pregnancies, availability of a dating scan between 8 to 14 weeks with AC less than 10th centile according to Hadlock GC on third trimester ultrasound with normal multi vessel Doppler studies who went on to deliver at term. All the women were of Indian origin. Exclusion criteria were major structural anomalies. With the postnatal birthweight being the gold standard with a cut off of <2.5kg being used to detect low birthweight the performance of each antenatal chart for the identification of small fetuses was evaluated using the parameters of sensitivity, specificity, positive predictive, negative predictive values and accuracy. The sensitivity for FMF GC was 69.2%, Mediscan GC 7.6%. The specificity for FMF GC was 40.5%, Mediscan GC 91.8%. The positive predictive value for FMF GC was 29%, Mediscan GC 25%, Hadlock 26%. The negative predictive value for FMF GC was 78.9%, Mediscan GC 73.9%. The accuracy for FMF GC was 48%, Mediscan GC 70%, Hadlock 26%. There is a wide variation in the sensitivity, specificity, positive predictive, negative predictive values and accuracy among the three antenatal GCs. Continued need for testing and monitoring performance in local population is needed to develop more localised or optimised growth charts.
DOI: 10.1002/uog.28377
Authors: S. Karri, M.A. Nallimelli, H. Prasad, V. Isukapalli, A. Gadipudi, S. Kapila
Institution: Logan Hospital
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4402360193