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Prediction of fetal macrosomia: effect of sonographic fetal weight‐estimation model and threshold used
Author(s) -
Melamed N.,
Yogev Y.,
Meizner I.,
Mashiach R.,
Pardo J.,
BenHaroush A.
Publication year - 2011
Publication title -
ultrasound in obstetrics and gynecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.202
H-Index - 141
eISSN - 1469-0705
pISSN - 0960-7692
DOI - 10.1002/uog.8930
Subject(s) - medicine , receiver operating characteristic , fetal weight , biometrics , fetus , sensitivity (control systems) , fetal macrosomia , statistics , pregnancy , mathematics , gestation , artificial intelligence , computer science , gestational diabetes , electronic engineering , biology , engineering , genetics
Objective To compare the accuracy of 21 sonographic fetal weight‐estimation models and abdominal circumference (AC) as a single measure for the prediction of fetal macrosomia (> 4000 g) using either fixed or optimal model‐specific thresholds. Methods A total of 4765 sonographic weight estimations performed within 3 days prior to delivery were analyzed. The predictive accuracy of 21 published sonographic fetal weight‐estimation models was calculated using three different thresholds: a fixed threshold of 4000 g; a model‐specific threshold obtained from the inflexion point of the receiver–operating characteristics (ROC) curve; and a model‐specific threshold associated with the highest overall accuracy. Cluster analysis was used to determine whether a certain combination of fetal biometric indices is associated with a higher predictive accuracy than others. Results For a fixed threshold of > 4000 g, there was considerable variation among the models in sensitivity (range, 13.6–98.5%) and specificity (range, 63.6–99.8%) for fetal macrosomia. Use of the threshold derived from the inflexion point of the ROC curve decreased the intermodel variation to a minimum (sensitivity, 84.4–91.4%; and specificity, 79.5–86.3%). Even when this optimal model‐specific threshold was applied, models based on three to four biometric indices were more accurate than were models based on only two biometric indices or on AC as a single measure ( P = 0.03). Conclusions Sonographic fetal weight‐estimation models based on three to four biometric indices appear to be more accurate than are models based on two indices or on AC as a single measure, for the diagnosis of macrosomia. In these cases, the use of an optimal, model‐specific threshold is associated with a higher degree of accuracy than is the uniform use of a fixed threshold of an estimated weight of > 4000 g. Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.