Development and external validation of a nomogram for predicting preterm birth at < 32 weeks in twin pregnancy

Abstract

The purpose of this study was to develop a dynamic model to predict the risk of spontaneous preterm birth at &lt; 32 weeks in twin pregnancy. A retrospective clinical study of consecutively asymptomatic women with twin pregnancies from January 2017 to December 2019 in two tertiary medical centres was performed. Data from one centre were used to construct the model, and data from the other were used to evaluate the model. Data on maternal demographic characteristics, transvaginal cervical length and funnelling during 20–24 weeks were extracted. The prediction model was constructed with independent variables determined by multivariate logistic regression analyses. After applying specified exclusion criteria, an algorithm with maternal and biophysical factors was developed based on 88 twin pregnancies with a preterm birth &lt; 32 weeks and 639 twin pregnancies with a delivery ≥ 32 weeks. It was then evaluated among 34 pregnancies with a preterm birth &lt; 32 weeks and 252 pregnancies with a delivery ≥ 32 weeks in a second tertiary centre without specific training. The model reached a sensitivity of 80.00%, specificity of 88.17%, positive predictive value of 50.33% and negative predictive value of 96.71%; ROC characteristics proved that the model was superior to any single parameter with an AUC of 0.848 (all P &lt; 0.005). We developed and validated a dynamic nomogram model to predict the individual probability of early preterm birth to better represent the complex aetiology of twin pregnancies and hopefully improve the prediction and indication of interventions.

Development and validation of a prediction model on spontaneous preterm birth in twin pregnancy: a retrospective cohort study

“…The odds ratios of the included risk variables in our nal models are consistent in both magnitude and direction with those reported in other studies [12,13,23,24].…”

“…Zhang Jun et al have developed a dynamic model to predict the risk of spontaneous preterm birth in twin pregnancies before 32 weeks of gestation. Their model demonstrated a sensitivity of 80.00%, speci city of 88.17%, positive predictive value of 50.33%, and negative predictive value of 96.71% [13]. In comparison, our model not only incorporates additional variables but also achieves discrimination in predicting sPTB.…”

“…Jun et al devised and validated two-stage nomogram models, incorporating mid-gestation clinical characteristics, for predicting individual risk of preterm birth at < 34 weeks in twin pregnancies, demonstrating robust discrimination, calibration, and positive clinical bene t [12]. Subsequently, the researchers developed and validated a dynamic nomogram model to accurately predict the individual risk of sPTB before 32 weeks in twin pregnancies [13]. Predicting the risk of preterm birth based on prepregnancy or rst trimester data holds greater signi cance for the implementation of interventions.…”

Ultrasonographic cervical length screening at 20–24 weeks of gestation in twin pregnancies for prediction of spontaneous preterm birth: A 10-year Taiwanese cohort

“…Current cervical length screening protocol, however, demonstrated only moderate predictive value even when taking into consideration funneling and monochorionicity, as evident from the results presented in Table 5 . This observation suggests the existence of unknown pathogenetic mechanisms specific to multiple pregnancies in the spontaneous onset of preterm birth [ 40 , 41 ]. Further research into the mechanisms of sPTB in twins is warranted.…”

Development and validation of a simplified risk prediction model for preterm birth: a prospective cohort study in rural Ethiopia

“…Ultrasound examinations 26 , 27 and biomarker tests 28 , 29 have been utilized to predict preterm birth, but these methods are less practical in resource-limited settings due to a lack of specialized medical equipment and trained health care providers 30 , 31 . Furthermore, existing studies on the prediction of preterm birth often exhibit limitations, such as lack of inclusivity of important prognostic factors 32 – 34 , focused on hospitalized women 35 – 38 or exclusively on multiple pregnancies 39 , 40 and reliance on high-level health care settings 33 , 34 . However, none of these studies were accurate enough to be applied in daily clinical practice in the primary care setting due to disparities in the potential predictors, domains, and levels of healthcare settings.…”