Predicting Progression from Gestational Diabetes to Impaired Glucose Tolerance Using Peridelivery Data: An Observational Study.
Am J Perinatol
; 2022 Sep 02.
Article
em En
| MEDLINE
| ID: mdl-35709723
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. STUDYDESIGN:
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..
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Am J Perinatol
Ano de publicação:
2022
Tipo de documento:
Article