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Acta Diabetologica

, Volume 53, Issue 3, pp 433–437 | Cite as

Development of a simple tool to predict the risk of postpartum diabetes in women with gestational diabetes mellitus

  • M. Köhler
  • A. G. ZieglerEmail author
  • A. Beyerlein
Original Article

Abstract

Aims

Women with gestational diabetes mellitus (GDM) have an increased risk of diabetes postpartum. We developed a score to predict the long-term risk of postpartum diabetes using clinical and anamnestic variables recorded during or shortly after delivery.

Methods

Data from 257 GDM women who were prospectively followed for diabetes outcome over 20 years of follow-up were used to develop and validate the risk score. Participants were divided into training and test sets. The risk score was calculated using Lasso Cox regression and divided into four risk categories, and its prediction performance was assessed in the test set.

Results

Postpartum diabetes developed in 110 women. The computed training set risk score of 5 × body mass index in early pregnancy (per kg/m2) + 132 if GDM was treated with insulin (otherwise 0) + 44 if the woman had a family history of diabetes (otherwise 0) − 35 if the woman lactated (otherwise 0) had R 2 values of 0.23, 0.25, and 0.33 at 5, 10, and 15 years postpartum, respectively, and a C-Index of 0.75. Application of the risk score in the test set resulted in observed risk of postpartum diabetes at 5 years of 11 % for low risk scores ≤140, 29 % for scores 141–220, 64 % for scores 221–300, and 80 % for scores >300.

Conclusions

The derived risk score is easy to calculate, allows accurate prediction of GDM-related postpartum diabetes, and may thus be a useful prediction tool for clinicians and general practitioners.

Keywords

Risk score Risk prediction Gestational diabetes Postpartum diabetes 

Notes

Acknowledgments

The authors thank Annette Knopff (Institute of Diabetes Research, Helmholtz Zentrum München), Sandra Hummel (Institute of Diabetes Research, Helmholtz Zentrum München), Melanie Bunk (Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München), and Martin Füchtenbusch (Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München) for their help in recruitment and follow-up and for their expert technical assistance. This work is partly based on the dissertation of Meike Köhler at the Ludwig-Maximilians-Universität München.

Funding

This study was supported by grants from the Helmholtz International Research Group (HIRG-0018) and the German Federal Ministry of Education and Research (BMBF) to the German Centre for Diabetes Research (DZD e.V.) and to the German Competence Net for Diabetes Mellitus (01GI0805).

Author contributions

MK analyzed the data and wrote the first and final drafts of the manuscript together with AB. AGZ designed the study, conceived the analysis, and critically revised the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Human and animal rights disclosure

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). The study was approved by the ethics committee of Bavaria, Germany (Bayerische Landesärztekammer Nr. 95357).

Informed consent disclosure

All patients gave written informed consent to participate in the study.

Supplementary material

592_2015_814_MOESM1_ESM.docx (29 kb)
Supplementary material 1 (DOCX 28 kb)

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Copyright information

© Springer-Verlag Italia 2015

Authors and Affiliations

  1. 1.Institute of Diabetes ResearchHelmholtz Zentrum MünchenNeuherbergGermany
  2. 2.Forschergruppe Diabetes, Klinikum rechts der IsarTechnische Universität MünchenNeuherbergGermany
  3. 3.Forschergruppe Diabetes e.V.NeuherbergGermany

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