Background: Concerns of COVID-19 vaccine safety from pregnant women still widespread. We used transcriptomic profile analysis to study changes of the maternal-fetal interface after vaccination and explore the possible protective effects from vaccination against miscarriage. Methods: We collected decidual tissuesafter uterine curettage from pregnant women in the first trimister with (n = 6) and without a COVID-19 vaccination (n = 6) and performed RNA-sequencing. Furthermore, we ananlyzed our transcriptome datas of samples and other datasets about maternal-fetal interface and miscarrige to analyze the potential link by bioinformatics tools. Results: We identified 879 different expressed genes from pregnant women who received vaccination and found that the COVID-19 vaccine could alter some hazardous RSA-related genes, such as CXCL11, FOS, FOSB, LY96, MMP10, and NCF2. Vaccination also changed some hazardous RSA-related signaling pathway.These molecules induced the transformation of M2 macrophages and promoted the balance of Th1/Th2 immune responses. Finally, these effects on the immune microenvironment of the maternal-fetal interface also showed corresponding positive changes. Conclusion: Many RSA-related signaling molecules were reversed after COVID-19 vaccination, indicating that the vaccine did not cause RSA, and these molecules ultimately may have protective effects on miscarriage by influencing the immune microenvironment at the maternal-fetal interface.

Objective: To develop and validate a predictive model assessing the risk of cesarean delivery in primiparous women based on the findings of magnetic resonance imaging (MRI) studies. Design: Observational study Setting: University teaching hospital. Population: 168 primiparous women with clinical findings suggestive of cephalopelvic disproportion. Methods: All women underwent MRI measurements prior to the onset of labor. A nomogram model to predict the risk of cesarean delivery was proposed based on the MRI data. The discrimination of the model was calculated by the area under the receiver operating characteristic curve (AUC) and calibration was assessed by calibration plots. The decision curve analysis was applied to evaluate the net clinical benefit. Main Outcome Measures: Cesarean delivery. Results: A total of 88 (58.7%) women achieved vaginal delivery, and 62 (41.3%) required cesarean section caused by obstructed labor. In multivariable modeling, the maternal body mass index before delivery, induction of labor, bilateral femoral head distance, obstetric conjugate, fetal head circumference and fetal abdominal circumference were significantly associated with the likelihood of cesarean delivery. The discrimination calculated as the AUC was 0.845 (95% CI: 0.783-0.908; P < 0.001). The sensitivity and specificity of the nomogram model were 0.918 and 0.629, respectively. The model demonstrated satisfactory calibration. Moreover, the decision curve analysis proved the superior net benefit of the model compared with each factor included. Conclusion: Our study provides a nomogram model that can accurately identify primiparous women at risk of cesarean delivery caused by cephalopelvic disproportion based on the MRI measurements.