Performance of early risk assessment tools to predict the later development of gestational diabetes
Open accessAbstract
Background: Several prognostic models for gestational diabetes mellitus (GDM) are provided in the literature; however, their clinical significance has not been thoroughly evaluated, especially with regard to application at early gestation and in accordance with the most recent diagnostic criteria. This external validation study aimed to assess the predictive accuracy of published risk estimation models for the later development of GDM at early pregnancy. Methods: In this cohort study, we prospectively included 1132 pregnant women. Risk evaluation was performed before 16 + 0 weeks of gestation including a routine laboratory examination. Study participants were followed‐up until delivery to assess GDM status according to the IADPSG 2010 diagnostic criteria. Fifteen clinical prediction models were calculated according to the published literature. Results: Gestational diabetes mellitus was diagnosed in 239 women, that is 21.1% of the study participants. Discrimination was assessed by the area under the ROC curve and ranged between 60.7% and 76.9%, corresponding to an acceptable accuracy. With some exceptions, calibration performance was poor as most models were developed based on older diagnostic criteria with lower prevalence and therefore tended to underestimate the risk of GDM. The highest variable importance scores were observed for history of GDM and routine laboratory parameters. Conclusions: Most prediction models showed acceptable accuracy in terms of discrimination but lacked in calibration, which was strongly dependent on study settings. Simple biochemical variables such as fasting glucose, HbA1c and triglycerides can improve risk prediction. One model consisting of clinical and laboratory parameters showed satisfactory accuracy and could be used for further investigations.
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The Benhalim-2 2020 model, which takes into account interview and biochemical data, showed the highest sensitivity.
“The Benhalim-2 2020 model, which takes into account interview and biochemical data (propensity score model: history of GDM, FPG, height, triglycerides, age, ethnic origin, first trimester weight, family history of diabetes, HbA1c), showed the highest sensitivity [36].”
From Gestational Diabetes Mellitus—Recent Literature Review (2022) · cites this paper as [36]
The Results section’s discrimination table lists the stated clinical and biochemical variables for Benhalima-2 2020 and gives it a ROC-AUC of 76.9%, the highest shown. The paper describes this as discrimination and reports superior net benefit; it does not establish that the model had the highest sensitivity. Page numbers are unavailable in our copy. (LLM, conf=0.87)
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- Authors
- Kotzaeridi, G., Blätter, J., Eppel, D., Rosicky, I., Mittlböck, M., Yerlikaya‐Schatten, G., Schatten, C., Husslein, P., Eppel, W., Huhn, E. A., Tura, A., & Göbl, C. S.
- Affiliations
- Medical University of Vienna (AT)
- University Hospital of Basel (CH)
- National Research Council (IT)
- Corresponding author
- Göbl, Christian S.
- ORCID
- Venue
- European Journal of Clinical Investigation
- Publisher
- Wiley
- Published
- 2021-06-18
- Volume
- 51
- Issue
- 12
- Pages
- e13630-e13630
- ISSN
- 0014-2972 (ISSN-L)
- 1365-2362
- PMC
- PMC9285036
- OpenAlex
- W3166238930
- Cited by
- 27
- References
- 40
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 5 · 2023: 6 · 2022: 5 · 2021: 3
- FWCI
- 4.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- European Journal of Clinical Investigation (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- gestational diabetes mellitus, risk prediction model, early pregnancy, external validation, IADPSG criteria, model calibration, discrimination (statistics), fasting blood glucose, HbA1c, triglycerides, risk assessment tools
- MeSH terms
- Obesity, Maternal, Pregnancy in Obesity, Adult, Blood Glucose, Blood Pressure, Ethnicity, Fasting, Female, Glycated Hemoglobin, Humans, Medical History Taking, Pregnancy, Prenatal Diagnosis, ROC Curve, Triglycerides, Cohort Studies, Diabetes, Gestational, Risk Assessment
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