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Am J Perinatol 2024; 41(S 01): e282-e289
DOI: 10.1055/a-1877-9587
Original Article

Predicting Progression from Gestational Diabetes to Impaired Glucose Tolerance Using Peridelivery Data: An Observational Study

Angela M. Bengtson 
1   Department of Epidemiology, Brown School of Public Health, Providence, Rhode Island
,
Ana Lucia Espinosa Dice
1   Department of Epidemiology, Brown School of Public Health, Providence, Rhode Island
,
Melissa A. Clark
2   Department of Health Services, Policy and Practice; Brown School of Public Health, Providence, Rhode Island
3   Department of Obstetrics and Gynecology, Women and Infants Hospital, The Warren Alpert Medical School of Brown University, Providence, Rhode Island
,
Roee Gutman
4   Department of Biostatistics, Brown School of Public Health, Providence, Rhode Island
,
Dwight Rouse
1   Department of Epidemiology, Brown School of Public Health, Providence, Rhode Island
3   Department of Obstetrics and Gynecology, Women and Infants Hospital, The Warren Alpert Medical School of Brown University, Providence, Rhode Island
,
Erika Werner
1   Department of Epidemiology, Brown School of Public Health, Providence, Rhode Island
3   Department of Obstetrics and Gynecology, Women and Infants Hospital, The Warren Alpert Medical School of Brown University, Providence, Rhode Island
› Institutsangaben Funding This work was supported by the National Institute of Mental Health (grant number: R00 MH112413) and the American Diabetes Association (grant number: 1-16-ICTS-118). The funding source had no involvement in the study design, analysis, or interpretation.
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Abstract

Objective This article aimed to develop a predictive model to identify persons with recent gestational diabetes mellitus (GDM) most likely to progress to impaired glucose tolerance postpartum.

Study Design We conducted an observational study among persons with GDM in their most recent pregnancy, defined by Carpenter-Coustan criteria. Participants were followed up from delivery through 1-year postpartum. We used lasso regression with k-fold cross validation to develop a multivariable model to predict progression to impaired glucose tolerance, defined as HbA1c≥5.7%, at 1-year postpartum. Predictive ability was assessed by the area under the curve (AUC), sensitivity, specificity, and positive and negative predictive values (PPV and NPV).

Results Of 203 participants, 71 (35%) had impaired glucose tolerance at 1-year postpartum. The final model had an AUC of 0.79 (95% confidence interval [CI]: 0.72, 0.85) and included eight indicators of weight, body mass index, family history of type 2 diabetes, GDM in a prior pregnancy, GDM diagnosis<24 weeks' gestation, and fasting and 2-hour plasma glucose at 2 days postpartum. A cutoff point of ≥ 0.25 predicted probability had sensitivity of 80% (95% CI: 69, 89), specificity of 58% (95% CI: 49, 67), PPV of 51% (95% CI: 41, 61), and NPV of 85% (95% CI: 76, 91) to identify women with impaired glucose tolerance at 1-year postpartum.

Conclusion Our predictive model had reasonable ability to predict impaired glucose tolerance around delivery for persons with recent GDM.

Key Points

  • We developed a predictive model to identify persons with GDM most likely to develop IGT postpartum.

  • The final model had an AUC of 0.79 (95% CI: 0.72, 0.85) and included eight clinical indicators.

  • If validated, our model could help prioritize diabetes prevention efforts among persons with GDM.

Keywords

gestational diabetes - impaired glucose tolerance - type 2 diabetes prevention - predictive model

Ethics Approval

All study participants provided written informed consent prior to data collection and ethical approval was provided by the Institutional Review Board, Women and Infants Hospital, Providence, Rhode Island, on January 6, 2016 (IRB no.: 836907).


Supplementary Material



Publikationsverlauf

Eingereicht: 22. Januar 2022

Angenommen: 03. Juni 2022

Accepted Manuscript online:
16. Juni 2022

Artikel online veröffentlicht:
02. September 2022

© 2022. Thieme. All rights reserved.

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333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

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