Factors Indicating the Accuracy of Fetal Weight Estimation in Preterm Newborns with Normal Amniotic Fluid Volume
DOI:
https://doi.org/10.21613/GORM.2019.1012Keywords:
Absolute percentage error, Estimated, Fetal weight, Inaccuracy rate, Prediction of birth weight, Preterm newbornAbstract
OBJECTIVE: To determine the factors indicating the accuracy of fetal weight estimation in the last prenatal ultrasonography before delivery in preterm newborns with normal amniotic fluid volume.
STUDY DESIGN: Three hundred and seventy-one singleton pregnancies with normal amniotic fluid volume and delivered at between 24+0 and 37+0 gestational weeks were evaluated in a retrospective study. Any possible associations between the absolute percentage error of fetal weight estimations and the maternal and fetal data were examined.
RESULTS: In 135 of the 371 women (36%), the absolute percentage error was greater than 10%. The mean absolute percentage error was 8.7±7.5%. The mean absolute percentage errors were 4.1±2.7% and 16.8±6.4% in the accurate and inaccurate estimation groups, respectively.
The rate of women examined during labor was significantly higher in the inaccurate estimation group compared to the accurate estimation group. There were no significant differences in age, body-mass-index, gestational age at delivery, estimated-fetal-weight, actual birth weight, days from the last ultrasound examination to delivery, small for gestational age rate, placenta localization or fetal presentation between the two groups.
Examination during labor (β=0.224) was the most important factor for the prediction of the absolute percentage error, followed by gestational age at delivery (β=–0.198), presence of (β=–0.158), and body-mass-index (β=0.142).
CONCLUSION: In 36% of our study population, the absolute percentage error was >10%. Examination during labor was the most important factor for the prediction of the absolute percentage error, followed by gestational age at delivery, presence of small for gestational age, and body-mass-index.
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Copyright (c) 2020 Onur Guralp, Nevin Tuten, Abdullah Tuten, Altay Gezer
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