Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women’s and Children’s Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.

This paper studies the multistage pricing and seat allocation problems for multiple train services in a high-speed railway (HSR) with multiple origins and destinations (ODs). Taking the maximum total revenue of all trains as the objective function, a joint optimization model of multistage pricing and seat allocation is established. The actual operation constraints, including train seat capacity constraints, price time constraints in each period, and price space constraints among products, are fully considered. We reformulate the optimization model as a bilevel multifollower programming model in which the upper-level model solves the seat allocation problem for all trains serving multiple ODs in the whole booking horizon and the lower optimizes the pricing decisions for each train serving each OD in different decision periods. The upper and lower are a large-scale static seat allocation programming and many small-scale multistage dynamic pricing programming which can be solved independently, respectively. The solving difficulty can be significantly reduced by decomposing. Then, we design an effective solution method based on divide-and-conquer strategy. A real instance of the China’s Wuhan-Guangzhou high-speed railway is employed to validate the advantages of the proposed model and the solution method.

ObjectiveTo compare the efficacy and safety of metformin, glyburide, and insulin for GDM, we conducted a subgroup analysis of outcomes for women with GDM according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) diagnostic criteria.MethodsWe searched the NCBI, Embase, and Web of Science databases from inception to March 2022. Randomized controlled trials (RCTs) that compared the outcomes of hypoglycemic agents in women with GDM were included. Bayesian network analysis was employed.ResultsA total of 29 RCTs were included. Metformin was estimated to lead to a slight improvement in total gestational weight gain (WMD – 1.24 kg, 95% CI −2.38, −0.09), a risk of unmet treatment target in the sensitivity analysis (OR 34.50, 95% CI 1.18–791.37) than insulin. The estimated effect of metformin showed improvements in birth weight than insulin (WMD – 102.58 g, 95% CI −180.45 to −25.49) and glyburide (WMD – 137.84 g, 95% CI −255.31 to −25.45), for hypoglycemia within 1 h of birth than insulin (OR 0.65, 95% CI 0.47 to 0.84). The improvement in the estimated effect of metformin for hypoglycemia within 1 h of birth still existed when compared with glyburide (OR 0.41, 95% CI 0.26 to 0.66), whether in the IADPSG group (OR 0.33, 95% CI 0.12 to 0.92) or not (OR 0.43, 95% CI 0.20 to 0.98).ConclusionMetformin is beneficial for GDM women to control total GWG compared with insulin, regulate fetal birth weight more than insulin and glyburide, and increase the risk of unmet treatment targets compared with insulin. Compared to metformin, glyburide is associated with neonatal hypoglycemia.

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