N Melamed1, Y Yogev, I Meizner, R Mashiach, J Pardo, A Ben-Haroush. 1. Helen Schneider Hospital for Women, Rabin Medical Center, Petah Tiqva, and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. nirm@clalit.org.il
Abstract
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.
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.
Authors: Gordon Cs Smith; Alexandros A Moraitis; David Wastlund; Jim G Thornton; Aris Papageorghiou; Julia Sanders; Alexander Ep Heazell; Stephen C Robson; Ulla Sovio; Peter Brocklehurst; Edward Cf Wilson Journal: Health Technol Assess Date: 2021-02 Impact factor: 4.014
Authors: Nir Melamed; Ahmet Baschat; Yoav Yinon; Apostolos Athanasiadis; Federico Mecacci; Francesc Figueras; Vincenzo Berghella; Amala Nazareth; Muna Tahlak; H David McIntyre; Fabrício Da Silva Costa; Anne B Kihara; Eran Hadar; Fionnuala McAuliffe; Mark Hanson; Ronald C Ma; Rachel Gooden; Eyal Sheiner; Anil Kapur; Hema Divakar; Diogo Ayres-de-Campos; Liran Hiersch; Liona C Poon; John Kingdom; Roberto Romero; Moshe Hod Journal: Int J Gynaecol Obstet Date: 2021-03 Impact factor: 3.561
Authors: Russell L Deter; Wesley Lee; Haleh Sangi-Haghpeykar; Adi L Tarca; Lami Yeo; Roberto Romero Journal: J Matern Fetal Neonatal Med Date: 2014-07-11
Authors: Alexandros A Moraitis; Norman Shreeve; Ulla Sovio; Peter Brocklehurst; Alexander E P Heazell; Jim G Thornton; Stephen C Robson; Aris Papageorghiou; Gordon C Smith Journal: PLoS Med Date: 2020-10-13 Impact factor: 11.069