Purpose: To investigate risk factors for preterm birth in twin pregnancies, and to establish a nomogram model for predicting preterm birth and verify its application value.
Methods: Data from 266 twin pregnancies between January 2015 and December 2020 were analyzed in this retrospective study. According to the gestational weeks of delivery, the included subjects were divided into a preterm birth group (gestational age < 37 weeks) and a full-term group (gestational age ≥ 37 weeks). The general situation and pregnancy complications of the two groups were analyzed by univariate analysis, and the factors with statistical significance were entered into multivariate logistic regression analysis. Furthermore, the nomogram model for predicting the risk of preterm birth was established by using R. The predictive effect of the model was evaluated by the area under the ROC curve, C-index, and decision curve analysis.
Results: Demographic characteristics and their associations with preterm birth and full-term birth in twin pregnancies were summarized and analyzed. After validation, we identified the following significant predictors of preterm birth: chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia. Overall, we constructed preterm risk nomogram model with C-index of 0.783. A nomogram using a 0-100 scale illustrated our final model for predicting preterm birth in twin pregnancies.
Conclusions: We developed and validated a clinical nomogram to predict preterm birth in twin pregnancy. Chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia were independent risk predictors for preterm birth in twin pregnancy.
Keywords: Preterm birth; nomogram; risk predictors; twin pregnancy.
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