Construction and validation of a novel nomogram for predicting spontaneous preterm birth in patients with gestational diabetes mellitus

Objective: To explore the influencing factors of spontaneous preterm birth (sPTB) in patients with gestational diabetes mellitus (GDM) and construct a nomogram model. Methods: A retrospective analysis was conducted on the clinical data of 289 GDM patients who gave birth at Yangzhou University Affiliated Hospital from January 2021 to December 2022. The patients were divided into the sPTB (n = 52) and non-sPTB (n = 237) groups based on whether sPTB occurred. Logistic multivariate analysis was used to explore the influencing factors of sPTB in GDM patients and construct a nomogram model. The predictive performance of the nomogram model was evaluated using ROC curves and calibration curves in internal validation. Additionally, 62 GDM patients who visited Yangzhou University Affiliated Hospital from January 2023 to June 2023 were retrospectively selected for external validation of the prediction model. Results: Logistic analysis showed that maternal age >= 30 years, pre-pregnancy BMI >= 26.3 kg/m(2), history of spontaneous abortion, premature rupture of membranes, and oral glucose tolerance test (OGTT) fasting blood glucose >= 5.1 mmol/L were independent risk factors for sPTB in GDM patients (all P<0.05). In internal validation, the AUC value of the model's ROC curve was 0.901, and in external validation, the AUC value was 0.939. The calibration curve showed that the predicted probability was consistent with the actual probability. In addition, the sensitivity, specificity, and accuracy of the model in external validation were 84.21%, 81.40%, and 82.26%, respectively. Conclusion: Maternal age >= 30 years, pre-pregnancy BMI >= 26.3 kg/m2, history of spontaneous abortion, premature rupture of membranes, and OGTT fasting blood glucose >= 5.1 mmol/L are independent risk factors for sPTB in GDM patients. The nomogram model based on these risk factors has high discrimination and accuracy in predicting sPTB in GDM patients.