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Archives of Gynecology and Obstetrics

, Volume 299, Issue 1, pp 97–103 | Cite as

Sonographic prediction of macrosomia in pregnancies complicated by maternal diabetes: finding the best formula

  • Anat Shmueli
  • Lina Salman
  • Eran Hadar
  • Amir Aviram
  • Ron Bardin
  • Eran Ashwal
  • Rinat Gabbay-Benziv
Maternal-Fetal Medicine
  • 65 Downloads

Abstract

Purpose

To evaluate the best performing formula for macrosomia prediction in pregnancies complicated by diabetes.

Methods

A retrospective analysis was performed of 1060 sonographic fetal biometrical measurements performed within 7 days of delivery in term pregnancies (37–42 gestational weeks) complicated by diabetes. Sonographic prediction of macrosomia (≥ 4000, ≥ 4250, and ≥ 4500 g) was evaluated utilizing ten previously published formulas by: (1) calculating for each macrosomia threshold the sensitivity, specificity, positive and negative predictive value, and ± likelihood ratio for macrosomia prediction; (2) comparing the systematic and random error and the proportion of estimates < 10% of birth weights between macrosomic and non-macrosomic neonates. Best performing formula was determined based on Euclidean distance.

Results

97 (9.2%) macrosomic neonates (> 4000 g) were included. Median birth weight was 3380 (1866–3998) g for non-macrosomic and 4198 (4000–5180) g for macrosomic neonates. Higher macrosomia cutoff was associated with higher specificity and lower sensitivity. We found a considerable variation between formulas in different accuracy parameters. Hadlock’s formula (1985), based on abdominal circumference, femur length, head circumference and biparietal diameter, had the shortest Euclidean distance, reflecting the highest accuracy.

Conclusion

Prediction of macrosomia among women with diabetes differs significantly between formulas. In our cohort, the best performing formula for macrosomia prediction was Hadlock’s formula (1985).

Keywords

Macrosomia Fetal weight estimation Diabetes in pregnancy 

Notes

Author contribution

AS: data collection and management, manuscript writing and editing, data analysis. LS: protocol development, manuscript editing. EH: protocol development, data management. A. Aviram: data collection and management, data analysis. RB: project development, data collection, manuscript editing. EA: project development, data collection. RG-B: project development, data collection, data analysis, manuscript editing.

Funding

None.

Compliance with ethical standards

Conflict of interest

None.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Obstetrics and GynecologyHelen Schneider Hospital for Women, Rabin Medical CenterPetah TikvaIsrael
  2. 2.The Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
  3. 3.Lis Maternity Hospital, Tel Aviv Sourasky Medical CenterTel AvivIsrael
  4. 4.Hillel Yaffe Medical CenterHaderaIsrael
  5. 5.The Rappaport Faculty of Medicine, TechnionHaifaIsrael

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