Objective: To investigate dysbiosis of the vaginal microbiota related to increased risk of preterm premature rupture of fetal membrane (PPROM) and chorioamnionitis in singleton gestations with ultrasound-indicated cerclage. Design: Retrospective observational study. Setting: Fujian Maternity and Child Health Hospital. Population: 44 singleton gestations with ultrasound-indicated cerclage, including 13 cases of PPROM and 31 cases of normal-term delivery. Methods: Composition of the vaginal microbiota was assessed prior to cervical cerclage at 18–24 weeks of gestation, using MiSeq-based 16S rRNA gene sequencing. Main Outcome Measures: To characterize the vaginal microbial profile of women who later experienced PPROM and chorioamnionitis. Results: Furthermore, the vaginal microbiota of women who later experienced PPROM was relatively enriched with Streptococcus anginosus and Prevotella timonensis (P=0.042, P=0.032, respectively), while that of women who later experienced normal-term delivery was relatively enriched with Lactobacillus. Further, enrichment for Prevotella was noted in patients diagnosed with chorioamnionitis in the PPROM group (6 of 13, 53.8%), which was absent in women with normal histology in the PPROM group (P=0.012). Conclusions: Together, these results indicate that dysbiosis of the vaginal microbiota is a risk element for subsequent PPROM and chorioamnionitis in singleton gestations with ultrasound-indicated cerclage. These findings may contribute to the development of methods to identify pregnancies at high risk for cerclage failure following PPROM. Funding: This work was supported by a grant from the Fujian Maternity and Child Health Hospital Innovation Project (YCXZ 18-21). Keywords: Vaginal microbiota, PPROM, chorioamnionitis, ultrasound-indicated cerclage, Prevotella.

Objective: The purpose of this study was to develop a dynamic nomogram model to predict the risk of spontaneous preterm birth at <32 weeks in twin pregnancy. Design: A retrospective analysis and multicentre validation study Setting and Population: Women with twin pregnancies followed up in two tertiary medical centres from January 2017 to March 2019. Methods: Data on maternal demographic characteristics, transvaginal cervical length and funneling were extracted. The prediction model was constructed with independent variables determined by logistic regression analyses. The risk score was calculated according to the dynamic nomogram model. Main outcome measures: The risk of spontaneous preterm birth at <32 weeks in twin pregnancy. Results: In total, 1065 twin pregnancies were eligible for the study, of which the data of 764 cases (92 twin preterm cases (<32 weeks) and 672 control cases) were obtained from a tertiary medical centre as the training group and those of 301 cases (36 twin preterm cases (<32 weeks) and 265 control cases) from the other tertiary medical centre as the external validation group. Based on logistic regression analyses, we built a dynamic nomogram model with satisfactory discrimination in both the training group(C-index: 0.856, 95% CI: 0.813-0.899) and external validation group(C-index: 0.808, 95% CI: 0.751-0.865). The restricted cubic splines and ROC curve supported the performance of the prediction model. Conclusions: We developed and validated a dynamic nomogram model to predict the individual probability of preterm birth in twin pregnancy at <32 weeks.