Objective Guidelines for screening and diagnosis of gestational diabetes mellitus (GDM) have been updated in the past several years, and various inconsistencies exist across these guidelines. Moreover, the quality of these updated guidelines has not been clarified. We thus conducted this systematic review to evaluate the relationship between the quality and detailed recommendations of these guidelines. Data sources The Guidelines International Network Library, the National Institute for Health and Clinical Excellence (NICE) database, the Medline database, the Embase and the National Guidelines Clearinghouse were searched for guidelines containing recommendations on screening and diagnosis strategies for GDM between 2009 and November 2018. Methods Guidelines included a target group of women with GDM, and contained recommendations for screening and diagnostic strategies for GDM were included in the present systematic review. Reviewers summarised recommendations on screening and diagnosis strategies from each guideline and rated the quality of guidelines by using the Appraisal of Guidelines Research and Evaluation (AGREE) criteria. Results A total of 459 citations were collected by the preliminary literature selection, and 16 guidelines that met the inclusion criteria were assessed. The inconsistencies of the guidelines mainly focus on the screening process (one step vs two step) and criteria of oral glucose tolerance test (OGTT) (International Association of Diabetes and Pregnancy Study Groups [IADPSG] vs CarpenterandCoustan). Guidelines with higher AGREE scores usually recommend a one-step OGTT strategy with IADPSG criteria between 24 and 28 gestational weeks, and the majority of these guidelines likely to select evidence by Grading of Recommendations Assessment, Development and Evaluation criteria. Conclusions The guidelines of WHO-2013, NICE-2015, American Diabetes Association-2018, Endocrine Society-2013, Society of Obstetricians and Gynaecologists of Canada-2016, International Federation of Gynecology and Obstetrics-2015, American College of Obstetricians and Gynecologists-2018, United States Preventive Services Task Force-2014 and IADPSG-2015 are strongly recommended in the present evaluation, according to the AGREE II criteria. Guidelines with higher quality tend to recommend a one-step 75 g OGTT strategy with IADPSG criteria between 24 and 28 gestational weeks.

To date, the miRNA expression profile of plasma exosomes in women whose pregnancy is complicated by gestational diabetes mellitus (GDM) has not been fully clarified. In this study, differentially expressed miRNAs in plasma exosomes were identified by high-throughput small-RNA sequencing in 12 pregnant women with GDM and 12 with normal glucose tolerance (NGT) and validated in 102 pregnant women with GDM and 101 with NGT. A total of 22 exosomal miRNAs were found, five of which were verified by real-time qPCR. Exosomal miR-423–5p was upregulated, whereas miR-122–5p, miR-148a-3p, miR-192–5p, and miR-99a-5p were downregulated in women whose pregnancy was complicated by GDM. IGF1R and GYS1 as target genes of miR-423–5p, and G6PC3 and FDFT1 as target genes of miR-122–5p were associated with insulin and AMPK signaling pathways and may participate in the regulation of metabolism in GDM. The five exosomal miRNAs had an area under the curve of 0.82 (95%CI, 0.73, ∼0.91) in early prediction of GDM. Our study demonstrates that dysregulated exosomal miRNAs in plasma from pregnant women with GDM might influence the insulin and AMPK signaling pathways and could contribute to the early prediction of GDM.

Background: The prevalence of both placenta previa and cesarean are on the rise. Multiple adverse outcomes are critically increased when placenta previa is subsequent to prior cesarean. The purpose of the present study is to develop a pre-surgical method for predicting adverse outcomes in pregnancy complicated with both placenta previa and prior cesarean. Methods: Clinical data was obtained from the medical history system at the First Affiliated Hospital of Sun Yat-sen University from February 2003 to December 2016. All cases with a final diagnosis of “placenta previa/low lying placenta (ICD:O44.001-105)” and “scarred uterus complicated with pregnancy (ICD: O34.200-202)” were collected and reviewed. Hysterectomy was taken as the primary outcome; and blood loss was taken as the secondary outcome. Results: Of 219 pregnant women in the final analysis, 25 received a hysterectomy following delivery, and 48 had blood loss exceeding 1000 ml. Pre-surgical risk factors for hysterectomy are ultrasonic signs of vascular lacunae, central placenta previa, and loss of normal hypoechoic retroplacental zone. A pre-surgical predictive equation referred to as “Hysterectomy Index in Placenta Previa with Prior cesarean (HIPs)” was generated and each risk factor was weighted to create an 8-point scale. This index yielded an area under the curve of 0.972 for the prediction of hysterectomy. Conclusions: Application of the HIPs score may provide an effective pre-surgical prediction of cesarean hysterectomy in pregnant women complicated with both placenta previa and prior cesarean.

Duration of second stage of labor is crucial for fetal delivery, but the optimal length of this stage remains controversial. While extending the duration of second stage can reduce primary cesarean delivery rates, it may increase maternal and neonatal morbidities as the duration progresses. We aimed to develop a personalized machine learning (ML) model to predict the possible second-stage duration. This multicenter, retrospective study was conducted at four tertiary hospitals in China from September 2013 to October 2022. Data from three hospitals in Guangdong Province was selected as derivation set, and a geographically independent dataset from Fujian Province as the external validation set. Singleton vaginal deliveries with term live birth in a cephalic position were included. The primary outcome was the duration of the second stage of labor. Since durations beyond 3 h were rare, we developed binary classification models with thresholds at 1 h and 2 h. After the optimal features selected by recursive feature elimination (RFE) method, four ML algorithms were employed to build the models. The best model would be selected with the predictive performance and interpreted with Shapley Additive exPlanations method. The study is registered in Clinical Trial (ChiCTR2400085338). Electronic medical records of 79,381 vaginal deliveries were obtained, and 63,401 deliveries meeting the inclusion criteria were included in the final analysis. Eight risk features were selected through the RFE process. Gradient boosting machine implemented by decision tree models achieved the best performance, yielding areas under the curve for 1-h and 2-h models of 0.808 (95% confidence interval [CI] 0.797–0.819) and 0.824 (95% CI 0.804–0.843) in the testing set, and 0.862 (95% CI 0.854–0.870) and 0.859 (95% CI 0.843–0.875) in the external validation set, respectively. An explainable and reliable ML model was developed to predict the probable second-stage duration, which could assist in individualized labor management. Factors such as first-stage duration and maternal age are potential predictors for the second stage. 10.13039/501100001809 National Natural Science Foundation of China (No.82371689, N0.81771602), and 10.13039/501100012166 National Key Research and Development Program of China (No.2021YFC2700703).

Fetal hypoxia is a leading cause of neonatal morbidity and mortality. Cardiotocography (CTG) is widely used to predict fetal hypoxia during labor, but its