Background: Neonatal respiratory failure (NRF) is the most common issue among premature and full-term infants admitted to the neonatal intensive care unit. The incidence rate and morbidity of NRF in clinical practice, especially in twin pregnancy, remain high. Methods: A total of 3,721 women with twin pregnancies were included in this retrospective study. The Lasso regression was employed to optimize the selection of relevant features. Following this, multivariate logistic regression analysis was utilized to construct a nomogram. The predictive performance of models was evaluated using the receiver operating characteristic (ROC) curve, calibration plot, and clinical decision curve. Furthermore, nine machine learning models were constructed for predicting NRF. Accuracy, precision, recall, F1 score, and ROC curve were used to evaluate the predictability of machine learning models. Results: The results of multivariate logistic regression analysis revealed that gestational age (GA), heparin, monochorionic monoamniotic (MCMA), placenta accreta, and placenta previa emerged as distinctive independent risk factors for NRF. Subsequently, a nomogram was constructed, incorporating these independent prognostic factors. In the training set, the nomogram exhibited the area under the curve (AUC) value of 0.908, while in the validation set, this metric remained high at 0.899. Among the machine learning models, long short-term memory (LSTM) and ensemble learning (EL) outshone the others, demonstrating the best performance with an AUC value of 0.91 in the validation set. The nomogram and machine learning models employed in this study demonstrated a robust and reliable predictive performance. Conclusions: The nomogram and machine learning models developed in this study prove to be effective and userfriendly tools for predicting the likelihood of NRF.

BACKGROUND:Accelerated industrialization globally has intensified air pollution, but the susceptibility periods for extreme air pollution in twin pregnancies remain undefined. METHODS:This study investigated the association between extreme air pollution exposure and preterm birth risk in twin pregnancies. Data on 3623 twin pregnancies in Chongqing from 2017 to 2022 and air pollution readings from 12 monitoring stations were analyzed using distributed lag non-linear quasi-Poisson regression models. Additionally, four extreme air pollution indices were developed to assess the cumulative effects of lagged exposures on preterm birth risk through multivariate logistic regression. RESULTS:Compared to the lower quartile, the 95th percentile of extreme air pollution exposure showed a positive correlation between concentrations of PM2.5, PM10, NO2, SO2 and CO and preterm birth risk in twin pregnancies, with O3 inversely correlated. Sensitive periods for air pollutants were different. 8-12 and 27-35 gestational weeks were identified for PM2.5; 6-13 and 27-35 gestational weeks were identified for PM10; 5-14 and 21-33 gestational weeks were identified for NO2; 4-15 and 24-36 gestational weeks were identified for SO2; 4-11 and 29-33 gestational weeks were identified for CO. PM2.5, PM10, SO2 and O3 showed cumulative effects across short and long lags, while CO showed a long-term effect. Notably, NO2 exhibited a protective effect during all lag periods. CONCLUSION:The study highlights gestational windows of 8-11 and 29-33 weeks as highly sensitive to extreme pollution for preterm birth in twin pregnancies, with marked risk increases during 0-3, 0-6 and 0-9-month lag periods.

Journal Article Accepted manuscript Deciphering the Link Between Hydroxychloroquine and SLE Materno-Fetal Health Get access Weizhen Tang, MD, Weizhen Tang, MD Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, 401147, China Search for other works by this author on: Oxford Academic PubMed Google Scholar Taihang Liu, PhD, Taihang Liu, PhD Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, 401147, China Correspondence: Tai-Hang Liu liuth@cqmu.edu.cn); Search for other works by this author on: Oxford Academic PubMed Google Scholar Xia Lan, MD Xia Lan, MD Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, 401147, China Xia Lan (18623177325@163.com) Search for other works by this author on: Oxford Academic PubMed Google Scholar Rheumatology, keae468, https://doi.org/10.1093/rheumatology/keae468 Published: 30 August 2024 Article history Received: 30 June 2024 Accepted: 01 July 2024 Published: 30 August 2024

BackgroundThe COVID-19 pandemic has significantly impacted healthcare systems worldwide, including obstetric care. However, the long-term effects on twin pregnancies remain unclear. This study investigates the impact of COVID-19 on the clinical characteristics and antibiotic prescribing patterns in hospitalized twin pregnancies.MethodsA retrospective cohort study was conducted at Women and Children’s Hospital of Chongqing Medical University, Chongqing, China, involving 3,827 twin pregnancies with live deliveries between 1 January 2017 and 31 December 2022. The pre-pandemic group included 1,707 patients, and the pandemic group included 2,120. Sociodemographic and clinical data were analyzed using general linear models with SPSS and R software.ResultsDuring the pandemic, twin pregnancy admissions increased by 24.19%. Patients in the pandemic group have less gestational weight gain (17.00 vs. 16.08 kg, P < 0.001), had higher rates of assisted reproductive technology use (73.2% vs. 68.7%, P = 0.002), and experienced more complications. Neonates showed higher rates of pneumonia (5.7% vs. 3.8%, P < 0.001) and NICU admissions (43.7% vs. 13.9%, P < 0.001). Longer hospital stays were observed in the pandemic group (P = 0.004). Antibiotic prescriptions, especially non-repeat prescriptions, increased for older patients, those with higher BMI, and premature deliveries. The rate of repeated antibiotic prescriptions for bacterial vaginosis increased 1.68 times.ConclusionCOVID-19 influenced twin pregnancy admissions, clinical characteristics, and antibiotic use. The study highlights the need for rational antibiotic use and improved healthcare resource management in future crises.

This cohort study assessed the stillbirth rate and neonatal comorbidities associated with the timing of delivery in twin pregnancies following in-vitro fertilization (IVF) treatments. This retrospective study encompassed 1596 twin pregnancies and categorized participants into spontaneous conception (SC) and IVF groups. The investigation initially assessed the impact of IVF on maternal and neonatal outcomes post-delivery, followed by an exploration of the prospective risk of stillbirth and incidence of stillbirth under IVF and gestational age stratification. Subsequently, multivariable Cox regression analysis was conducted to determine any significant difference in twin mortality with or without IVF. Additionally, post-delivery maternal and neonatal comorbidities rates are examined within the context of IVF and gestational age categories using multivariable logistic regression and restricted cubic splines to investigate trends in neonatal comorbidities with and without IVF. The objective was to optimize delivery timing to balance the risk of stillbirth associated with continued pregnancy against the risks of late preterm birth and neonatal complications, thereby achieving the best possible maternal and infant health outcomes. The study revealed that twin pregnancies conceived through IVF were associated with higher maternal age and pre-pregnancy body mass index (PBMI) compared to the SC group, yet there were no significant differences in the incidence of maternal and neonatal outcomes post-delivery. While the prospective risk of stillbirth and the rate of stillbirth was higher in the IVF group at each delivery time point, these differences are not statistically significant after adjusting for confounding factors in the Cox regression analysis. The incidence of post-delivery maternal and neonatal outcomes in the IVF group was not significantly different from the SC group across various delivery times and after adjustment using logistic regression and restricted cubic splines, gestational age significantly affected the risk of composite neonatal outcomes (p < 0.05). In the IVF group, compared to a median gestational age of 37 weeks, both late preterm and pregnancies delivered beyond 37 weeks showed an increasing trend in the risk of composite neonatal outcomes. Conversely, in the SC group, the risk of composite neonatal outcomes showed a decreasing trend with the extension of gestational weeks at delivery. In twin pregnancies resulting from IVF treatment, both the prospective risk of stillbirth and the rate of stillbirth were higher compared to those in the SC group. Considering the associated risks of stillbirth and neonatal complications, delivery around 37 weeks may be associated with more favorable outcomes. However, this observation does not establish 37 weeks as the definitive optimal time for delivery. The findings suggest that further research is needed to explore the best delivery timing for IVF twin pregnancies and to guide clinical decision-making for optimizing pregnancy outcomes.

Investigate the association between Oral Glucose Tolerance Test (OGTT) after in vitro fertilization (IVF) treatment and adverse maternal and neonatal outcomes in twin pregnancies. This retrospective study encompassed 2,541 twin pregnancies conceived through IVF treatment. Adverse maternal and neonatal outcomes were compared across different subgroups based on individual and combined OGTT classifications. A Spearman correlation regression model examined associations between OGTT levels at different time points and parameters such as gestational age, birth weight, and length. Subsequently, a Logistic regression model with restricted cubic splines (RCS) explored the relationships between OGTT levels at different time points and adverse pregnancy outcomes. Ultimately, nine types of machine learning models were developed using OGTT glucose values at different times to predict the risk of adverse pregnancy outcomes. In subgroup analysis based on individual OGTT diagnosis, three time points were examined: fasting glucose (OGTT0), 1-hour post-glucose (OGTT1), and 2-hour post-glucose (OGTT2). OGTT0 ≥ 5.1 mmol/L was significantly associated with increased risks of ICP and neonatal hypoglycemia (p = 0.031; p = 0.022). OGTT1 ≥ 10 mmol/L correlated with higher risks of ICP and neonatal hyperbilirubinemia (p = 0.001; p = 0.002). OGTT2 ≥ 8.5 mmol/L was also linked to neonatal hyperbilirubinemia (p < 0.001). In combined impaired OGTT subgroups, the impaired fasting glucose (IFG) group had a higher incidence of neonatal hypoglycemia than the impaired glucose tolerance (IGT) group and IFG IGT group, but a lower risk of neonatal hyperbilirubinemia. OGTT2 was negatively correlated with gestational age at delivery (β = - 0.08, p = 0.018), and both OGTT1 and OGTT2 were negatively correlated with neonatal birth weight (β = - 10.54, p = 0.008; β = - 15.04, p < 0.001), as well as OGTT2 with birth length (β = - 0.16, p = 0.009). The RCS logistic regression model indicated that the increase OGTT values was associated with the ICP risk, and the relationship between OGTT2 and neonatal hyperbilirubinemia was U-shaped. Among the various machine learning models predicting adverse outcomes, RandomForest exhibited superior performance. OGTT values in twin pregnancies under IVF treatment are closely linked to adverse maternal and neonatal outcomes, with post-load glucose levels potentially serving as an early biomarker for identifying poorer outcomes. The inflection points in the RCS suggest a new indication point for the association between OGTT and adverse pregnancy outcomes in twin pregnancies conceived through IVF.

Purpose:This study aimed to systematically evaluate the quality of content and information in videos related to gestational diabetes mellitus on Chinese social media platforms. Methods:The videos on various platforms, TikTok, Bilibili, and Weibo, were searched with the keyword "gestational diabetes mellitus" in Chinese, and the first 50 videos with a comprehensive ranking on each platform were included for subsequent analysis. Characteristic information of video was collected, such as their duration, number of days online, number of likes, comments, and number of shares. DISCREN, JAMA (The Journal of the American Medical Association) Benchmark Criteria, and GQS (Global Quality Scores) were used to assess the quality of all videos. Finally, the correlation analysis was performed among video features, video sources, DISCERN scores, and JAMA scores. Results:Ultimately, 135 videos were included in this study. The mean DISCERN total score was 31.84 ± 7.85, the mean JAMA score was 2.33 ± 0.72, and the mean GQS was 2.00 ± 0.40. Most of the videos (52.6%) were uploaded by independent medical professionals, and videos uploaded by professionals had the shortest duration and time online (P < 0.001). The source of the video was associated with numbers of "likes", "comments", and "shares" for JAMA scores (P < 0.001), but there was no correlation with DISCERN scores. Generally, videos on TikTok with the shortest duration received the most numbers of "likes", "comments", and "shares", but the overall quality of videos on Weibo was higher. Conclusion:Although the majority of the videos were uploaded by independent medical professionals, the overall quality appeared to be poor. Therefore, more efforts and actions should be taken to improve the quality of videos related to gestational diabetes mellitus.

Background Previous studies have confirmed that in-vitro fertilization (IVF) is associated with higher risks of placenta abnormalities and complications. Considering the increased risk of twin and higher-order multiple pregnancies, we tried to investigate the association between IVF and the risk of placenta outcomes in twin pregnancies. Methods This retrospective cohort study included 3845 cases of twin pregnancies delivered at Chongqing Health Center for Women and Children (CQHCWC) between 2017 and 2022. Poisson regression modeling with restricted cubic splines of exact maternal age was used to estimate the absolute risk of placenta outcomes in IVF and non-IVF groups. Main outcomes include placenta abnormalities (placenta previa, placental abruption, placenta accrete, and abnormal morphology of placenta) and placenta-related complications (gestational hypertension, preeclampsia, eclampsia, preterm birth, fetal distress, and fetal growth restriction (FGR)). To dissect the influence of chorionicity on the results, we further did the same analysis on the mono- and di-chorionic sub-group. Results The absolute risk of placenta previa, placenta accreta, placental abruption, gestational hypertension, and preeclampsia are significantly higher in the IVF group than in the non-IVF group. While there are no significant differences in the absolute risk of abnormal placenta morphology, fetal distress, FGR, and preterm birth between the two groups. After we did further analysis on the dichorionic sub-group, we found the absolute risk of preterm birth was also higher in the IVF group than in the non-IVF group. Conclusions Twin pregnancies who received IVF treatment have a higher risk for most kinds of placenta abnormalities and placenta-related complications. Whether these risks have any further impact on maternal and fetal health needs further investigation.

Purpose To evaluate the effect of intrahepatic cholestasis of pregnancy (ICP) with gestational diabetes mellitus (GDM) on perinatal outcomes and establish a prediction model of adverse perinatal outcomes in women with ICP. Methods This multicenter retrospective cohort study included the clinical data of 2,178 pregnant women with ICP, including 1,788 women with ICP and 390 co-occurrence ICP and GDM. The data of all subjects were collected from hospital electronic medical records. Univariate and multivariate logistic regression analysis were used to compare the incidence of perinatal outcomes between ICP with GDM group and ICP alone group. Results Baseline characteristics of the population revealed that maternal age ( p < 0.001), pregestational weight ( p = 0.01), pre-pregnancy BMI ( p < 0.001), gestational weight gain ( p < 0.001), assisted reproductive technology (ART) ( p < 0.001), and total bile acid concentration ( p = 0.024) may be risk factors for ICP with GDM. Furthermore, ICP with GDM demonstrated a higher association with both polyhydramnios (OR 2.66) and preterm labor (OR 1.67) compared to ICP alone. Further subgroup analysis based on the severity of ICP showed that elevated total bile acid concentrations were closely associated with an increased risk of preterm labour, meconium-stained amniotic fluid, and low birth weight in both ICP alone and ICP with GDM groups. ICP with GDM further worsened these outcomes, especially in women with severe ICP. The nomogram prediction model effectively predicted the occurrence of preterm labour in the ICP population. Conclusions ICP with GDM may result in more adverse pregnancy outcomes, which are associated with bile acid concentrations.

Background and aims: Intrahepatic cholestasis of pregnancy (ICP) is a special liver disease during pregnancy, characterized by abnormal bile acid metabolism. However, there is no consensus on how to group women with ICP based on the time of diagnosis worldwide. This study aimed to adopt a new grouping model of women with ICP, and the time from diagnosis to delivery was defined as the monitoring period. Methods: This retrospective real-world data study was conducted across multiple centers and included 3172 women with ICP. The study first evaluated the significant difference in medication and nonmedication during different monitoring times. The least absolute shrinkage and selection operator (LASSO) model was then used to screen nine risk factors based on the predictors. The model's discrimination, clinical usefulness, and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve, and calibration analysis. Results: The incidence of preeclampsia risk in ICP patients without drug intervention increased with the extension of the monitoring period. However, the risk of preeclampsia decreased in ICP patients treated with ursodeoxycholic acid. A predictive nomogram and risk score model was developed based on nine risk factors. The area under the ROC curve of the nomogram was 0.765 [95% confidence interval (CI): 0.724–0.807] and 0.812 (95% CI: 0.736–0.889) for the validation cohort. Conclusions: This study found that a longer ICP monitoring period could lead to adverse pregnancy outcomes in the absence of drug intervention, especially preeclampsia. A predictive nomogram and risk score model was developed to better manage ICP patients, maintain pregnancy to term delivery, and minimize the risk of severe adverse maternal and fetal outcomes.

Coronavirus disease-2019 (COVID-19) has caused continuous effects on the global public, especially for susceptible and vulnerable populations like pregnant women. COVID-19-related studies and publications have shown blowout development, making it challenging to identify development trends and hot areas by using traditional review methods for such massive data. Aimed to perform a bibliometric analysis to explore the status and hotspots of COVID-19 in obstetrics. An online search was conducted in the Web of Science Core Collection (WOSCC) database from January 01, 2020 to November 31, 2022, using the following search expression: (((TS= (“COVID 19” OR “coronavirus 2019” OR “coronavirus disease 2019” OR “SARS-CoV-2” OR “2019-nCoV” OR “2019 novel coronavirus” OR “SARS coronavirus 2” OR “Severe Acute Respiratory Syndrome Coronavirus-2” OR “SARS-COV2”)) AND TS= (“obstetric*” OR “pregnancy*” OR “pregnant” OR “parturition*” OR “puerperium”))). VOSviewer version 1.6.18, CiteSpace version 6.1.R6, R version 4.2.0, and Rstudio were used for the bibliometric and visualization analyses. 4144 articles were included in further analysis, including authors, titles, number of citations, countries, and author affiliations. The United States has contributed the most significant publications with the leading position. “Sahin, Dilek” has the largest output, and “Khalil, Asma” was the most influential author with the highest citations. Keywords of “Cov,” “Experience,” and “Neonate” with the highest frequency, and “Systematic Review” might be the new research hotspots and frontiers. The top 3 concerned genes included ACE2, CRP, and IL6. The new research hotspot is gradually shifting from the COVID-19 mechanism and its related clinical research to reviewing treatment options for pregnant women. This research uniquely delves into specific genes related to COVID-19’s effects on obstetrics, a focus that has not been previously explored in other reviews. Our research enables clinicians and researchers to summarize the overall point of view of the existing literature and obtain more accurate conclusions.

BackgroundTraditional fixed thresholds for oral glucose tolerance test (OGTT) results may inadequately prevent adverse pregnancy outcomes in twin pregnancies. This study explores latent OGTT patterns and their association with adverse outcomes.MethodsThis study retrospectively analyzed 2644 twin pregnancies using latent mixture models to identify glucose level patterns (high, HG; medium, MG; and low, LG) and their relationship with maternal/neonatal characteristics, gestational age at delivery, and adverse outcomes.ResultsThree distinct glucose patterns, HG, MG, and LG patterns were identified. Among the participants, 16.3% were categorized in the HG pattern. After adjustment, compared with the LG pattern, the HG pattern was associated with a 1.79-fold, 1.66-fold, and 1.32-fold increased risk of stillbirth, neonatal respiratory distress, and neonatal hyperbilirubinemia, respectively. The risk of neonatal ICU admission for MG and HG patterns increased by 1.22 times and 1.32 times, respectively, compared with the LG pattern. As gestational weeks increase, although there is an overlap in the confidence intervals between the HG pattern and other patterns in the restricted cubic splines analysis, the trend suggests that pregnant women with the HG pattern are more likely to face risks of their newborns requiring neonatal intensive care unit admission, and adverse comprehensive outcomes, compared with other patterns. In addition, with age and body mass index increasing in HG mode, gestation weeks at delivery tend to be later than in other modes.ConclusionDistinct OGTT glucose patterns in twin pregnancies correlate with different risks of adverse perinatal outcomes. The HG pattern warrants closer glucose monitoring and targeted intervention. imageConclusionDistinct OGTT glucose patterns in twin pregnancies correlate with different risks of adverse perinatal outcomes. The HG pattern warrants closer glucose monitoring and targeted intervention. image

PurposeThis study aimed to investigate the impacts of home quarantine on pregnancy outcomes of women with intrahepatic cholestasis of pregnancy (ICP) during the COVID-19 outbreak and whether the rational use of drugs will change these impacts.MethodsThis multi-center study was conducted to compare the pregnancy outcomes in women with ICP between the home quarantine group and the non-home quarantine group in southwest China. Propensity score matching was performed to confirm the pregnancy outcomes of the medication group and the non-medication group in women with ICP during the epidemic period.ResultsA total of 3,161 women with ICP were enrolled in this study, including 816 in the home quarantine group and 2,345 in the non-home quarantine group. Women with ICP in the home quarantine group had worse pregnancy outcomes, such as a growing risk of gestational diabetes mellitus A1, fetal growth restriction, pre-eclampsia, preterm delivery, and even stillbirth. Drug therapy could alleviate some adverse pregnancy outcomes caused by home quarantine, including pre-eclampsia, preterm delivery, and meconium-stained amniotic fluid.ConclusionCOVID-19 quarantine would increase the incidence of ICP and lead to adverse pregnancy outcomes in women with ICP. The rational use of drugs reduced some obstetrical complications and improved partial pregnancy outcomes. Our findings suggested that the government and hospitals should enhance their management and life guidance for women with ICP and speed up developing home quarantine guidelines.

There is a lack of data on gestational weight gain (GWG) in twin pregnancies. We divided all the participants into two subgroups: the optimal outcome subgroup and the adverse outcome subgroup. They were also stratified according to prepregnancy body mass index (BMI): underweight (< 18.5 kg/m 2 ), normal weight (18.5–23.9 kg/m 2 ), overweight (24–27.9 kg/m 2 ), and obese (≥ 28 kg/m 2 ). We used 2 steps to confirm the optimal range of GWG. The first step was proposing the optimal range of GWG using a statistical-based method (the interquartile range of GWG in the optimal outcome subgroup). The second step was confirming the proposed optimal range of GWG via compared the incidence of pregnancy complications in groups below or above the optimal GWG and analyzed the relationship between weekly GWG and pregnancy complications to validated the rationality of optimal weekly GWG through logistic regression. The optimal GWG calculated in our study was lower than that recommended by the Institute of Medicine. Except for the obese group, in the other 3 BMI groups, the overall disease incidence within the recommendation was lower than that outside the recommendation. Insufficient weekly GWG increased the risk of gestational diabetes mellitus, premature rupture of membranes, preterm birth and fetal growth restriction. Excessive weekly GWG increased the risk of gestational hypertension and preeclampsia. The association varied with prepregnancy BMI. In conclusion, we provide preliminary Chinese GWG optimal range which derived from twin-pregnant women with optimal outcomes(16–21.5 kg for underweight, 15–21.1 kg for normal weight, 13–20 kg for overweight), except for obesity, due to the limited sample size.