Background. Placenta accreta spectrum (PAS) disorders seriously threaten the safety of the mother and infant in the perinatal period. Moreover, PAS is associated with poor maternal and perinatal outcomes once complicated with cervical implantation. Dismally, there are few reports about PAS complicated with cervical involvement currently, and the early warning models are also rarely reported. To screen the risk factors of PAS complicated with cervical implantation and construct an early risk warning model, we performed the analysis of clinical indicators and images of PAS patients by artificial intelligence (AI) data processing methods. Methods. The clinical data of 166 patients with PAS in our hospital from January 2016 to September 2020 were retrospectively analyzed. The patients were divided into cervical implantation group and lower uterine implantation group according to the position of placenta implantation. Then, we compared the pregnancy outcomes of the two groups, screened the possible related factors of PAS complicated with cervical implantation by univariate analysis, and established the early warning model by logistic regression analysis. Results. The maternal outcome of PAS complicated with cervical implantation was worse than that of the lower uterine implantation group. Through univariate analysis and logistic regression analysis, we found that the cervical width, abundant cervical blood flow, and bladder line interruption were all risk factors of PAS complicated with cervical implantation, and their contribution to the establishment of the regression model was statistically significant. Conclusion. PAS complicated with cervical implantation was extremely severe. Early identification of risk factors and establishment of a risk warning model have certain guiding significance for clinical formulation of a reasonable treatment plan.

Background. Forceps delivery is one of the most important measures to facilitate vaginal delivery. It can reduce the rate of first cesarean delivery. Frustratingly, adverse maternal and neonatal outcomes associated with forceps delivery have been frequently reported in recent years. There are two major reasons: one is that the abilities of doctors and midwives in forceps delivery vary from hospital to hospital and the other one is lack of regulations in the management of forceps delivery. In order to improve the success rate of forceps delivery and reduce the incidence of maternal and neonatal complications, we applied form-based management to forceps delivery under an intelligent medical model. The aim of this work is to explore the clinical effects of form-based management of forceps delivery. Methods. Patients with forceps delivery in Maternal and Child Health Hospital Affiliated to Nanchang University were divided into two groups: form-based patients from January 1, 2019, to December 31, 2020, were selected as the study group, while traditional protocol patients from January 1, 2017, to December 31, 2018, were chosen as the control group. Then, we compared the maternal and neonatal outcomes of these two groups. Results. There were significant differences in the maternal and neonatal adverse outcomes such as rate of postpartum hemorrhage, degree of perineal laceration, and incidence of neonatal facial skin abrasions between the two groups, whereas differences in the incidence of asphyxia and intracranial hemorrhage were not significant. Conclusions. Form-based management could help us assess the security of forceps delivery comprehensively, as it could not only improve the success rate of the one-time forceps traction scheme but also reduce the incidence of maternal and neonatal adverse outcomes effectively.

Background. In a global environment of increasing cesarean delivery rate, promoting vaginal delivery, reducing the rate of first cesarean section, and the incidence of vaginal delivery complications are the objectives of obstetric medical quality and safety in China. As a common obstetric complication, preeclampsia affects the safety of many pregnant women. It is the obstetricians great responsibility to promote vaginal delivery and improve delivery outcomes in preeclampsia. To this end, we explored the roles of active labor management under the smart medical model in improving the outcomes of vaginal delivery for pregnant women with preeclampsia. Methods. The clinical data of 219 cases of preeclampsia pregnant women who delivered vaginally in our hospital from January 2017 to December 2020 were retrospectively analyzed. According to different labor process management, they were divided into study group (active labor process management group) and control group (normal labor process management group). Active labor process management methods included intrapartum ultrasound, central fetal heart rate monitoring, Doula delivery, labor analgesia, and quality of life care. The differences in delivery process, delivery outcome, bleeding causes, and hemostatic measures were compared between the two groups. Results. (1) The incidence of preeclampsia in our hospital showed an increasing trend in recent four years; (2) in smart hospitals, the active management of labor process reduced the probability of transferring to the cesarean section in preeclampsia pregnant women with vaginal trial failure; and (3) active labor process management reduced the rate of lateral episiotomy, decreased the postpartum hemorrhage volume within two hours, and improved the vaginal delivery outcome of preeclampsia pregnant women. Conclusions. In the era of the rapid development of the Internet, vigorously promoting the construction of smart hospitals and actively managing the delivery process can reduce the failure rate of vaginal trial delivery and improve the outcomes of vaginal delivery in preeclampsia women.

Preterm labor is a common high-risk condition during pregnancy, but current diagnostic approaches, such as cervical length measurement and uterine contraction monitoring, lack sufficient specificity and sensitivity. This study aims to explore potential biomarkers for threatened preterm labor using untargeted metabolomics, providing novel indicators to improve clinical diagnosis. A total of 46 pregnant women from Jiangxi Maternal and Child Health Hospital were retrospectively enrolled in case–control study and divided into a preterm birth group (n = 23) and a control group (n = 23) based on gestational age. Serum metabolic profiles were analyzed using untargeted metabolomics. Differential metabolites were identified via Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and P-value screening. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to explore their biological relevance. Logistic regression and Receiver Operating Characteristic (ROC) curve analysis were applied to evaluate potential biomarkers for threatened preterm labor. Using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), key metabolites associated with preterm birth were identified, including cis-9-palmitoleic acid (AUC = 0.830), 2-amino-1-phenylethanol (AUC = 0.718), and phenylalanine (AUC = 0.708), as shown by ROC curves. These metabolites were significantly elevated in the preterm group and showed good diagnostic potential (AUC > 0.5). Several serum metabolites were identified as potential biomarkers for threatened preterm labor, defined by regular uterine contractions, cervical changes, and abnormal vaginal discharge before 37 weeks. These findings may aid in the early diagnosis of preterm birth.

To explore the cytochrome P450 family 27 subfamily A member 1 (CYP27A1) gene mutations in Chinese women with intrahepatic cholestasis of pregnancy (ICP) and the correlation between CYP27A gene muta...