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Archives of Gynecology and Obstetrics

, Volume 298, Issue 1, pp 67–74 | Cite as

Fetal overgrowth in pregnancies complicated by diabetes: development of a clinical prediction index

  • Tracy M. Tomlinson
  • Dorothea J. Mostello
  • Kee-Hak Lim
  • Jennifer S. Pritchard
  • Gil Gross
Maternal-Fetal Medicine
  • 119 Downloads

Abstract

Purpose

To develop an index to predict fetal overgrowth in pregnancies complicated by diabetes.

Methods

Data were derived from a cohort of 275 women with singleton gestations in a collaborative diabetes in pregnancy program. Regression analysis incorporated clinical factors available in the first 20–30 weeks of pregnancy that were assigned beta-coefficient-based weights, the sum of which yielded a fetal overgrowth index (composite score).

Results

Fifty-one (18.5%) pregnancies were complicated by fetal overgrowth. The derived index included five clinical factors: age ≤ 30, history of macrosomia, excessive gestational weight gain, enlarged fetal abdominal circumference, and fasting hyperglycemia. Area under the curve (AUC) for the index is 0.88 [95% confidence interval (CI) 0.82–0.92]. Cut-points were selected to identify “high-risk” and “low-risk” ranges (≥ 8 and ≤ 3) that have positive and negative predictive values of 84% (95% CI 70–98%) and 95% (95% CI 92–98%), respectively. The majority of women in our cohort (n = 182, 66%) had a “low-risk” index while 9% (n = 25) had a “high-risk” index. Sub-analyses of nulliparous women and women with gestational and pre-gestational diabetes revealed that the overgrowth index was equally or more predictive when applied separately to each of these groups.

Conclusion

This fetal overgrowth index that incorporates five clinical factors provides a means of predicting fetal overgrowth and thereby serves as a tool for targeting the allocation of healthcare resources and treatment individualization.

Keywords

Birthweight Diabetes Large-for-gestational age Macrosomia Prediction 

Notes

Acknowledgements

We would like to thank Lea Bouchard, Gayle Davidson, and Wendy Barrett, South Shore Hospital, for assistance with data collection.

Author contributions

TT: protocol/project development, data collection and management, data analysis, and manuscript writing/editing. DM: manuscript writing/editing. KHL: manuscript writing/editing. JP: data collection or management. GG: manuscript writing/editing.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

For this type of study formal consent is not required. Ethics approval was obtained from the Institutional Review Board at South Shore Hospital (Weymouth, MA) on 4/10/2012 (SSH-ID#12-006). A waiver of consent was approved because the study involved the development of a prediction index using anonymised medical chart data that had been routinely collected. The only risk to patients was potential breach of confidentiality which was minimized by use of a password-protected database and a code to protect patient confidentiality. The key to the code was kept separate from the data and destroyed at the completion of the data analysis.

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Copyright information

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

Authors and Affiliations

  1. 1.Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Women’s HealthSaint Louis University School of MedicineSaint LouisUSA
  2. 2.Department of Obstetrics and GynecologyBoston Maternal-Fetal Medicine, South Shore HospitalWeymouthUSA
  3. 3.New England Quality Care AllianceBraintreeUSA

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