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Development and validation of a risk prediction model for preterm birth in women with gestational diabetes mellitus
Hanbing Li1, Lingling Gao2, Xiao Yang2
1School of Nursing, University of South China, Hengyang, Hunan, China.
Objectives:
This study aims to develop and validate a prediction model for preterm birth in women with gestational diabetes mellitus (GDM).
Design:
We conducted a retrospective study on women with GDM who gave birth at the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, between November 2017 and July 2021. We divided 1879 patients into a development set (n = 1346) and a validation set (n = 533). The development set was used to construct the prediction model for preterm birth using the stepwise logistic regression model. A nomogram and a web calculator were established based on the model. Discrimination and calibration were assessed in both sets.
Patients And Measurements:
Patients were women with GDM. Data were collected from medical records. GDM was diagnosed with 75-g oral glucose tolerance test during 24-28 gestational weeks. Preterm birth was definied as gestational age at birth <37 weeks.
Results:
The incidence of preterm birth was 9.4%. The predictive model included age, assisted reproductive technology, hypertensive disorders of pregnancy, reproductive system inflammation, intrahepatic cholestasis of pregnancy, high-density lipoprotein, homocysteine, and fasting blood glucose of 75-g oral glucose tolerance test. The area under the receiver operating characteristic curve for the development and validation sets was 0.722 and 0.632, respectively. The model has been adequately calibrated using a calibration curve and the Hosmer-Lemeshow test, demonstrating a correlation between the predicted and observed risk.
Conclusion:
This study presents a novel, validated risk model for preterm birth in pregnant women with GDM, providing an individualized risk estimation using clinical risk factors in the third trimester of pregnancy.
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