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Although there is a high rate of pregnant immigrant women in Korea, little is known regarding their pregnancy outcomes. The aim of this study was to evaluate the pregnancy outcomes of immigrant women in Korea. Data for all pregnant women who gave birth between January 1, 2007 and December 31, 2016 were obtained using the Health Insurance Review and Assessment Service Database. Pregnant women were divided into two groups: Korean and immigrant women. The main outcome measures were adverse pregnancy outcomes including gestational diabetes of mellitus, preeclampsia, cesarean section, placental abrnomalities, and postpartum hemorrhage. The odds of gestational diabetes mellitus, preeclampsia, cesarean section, placental previa, placental abruptio, and postpartum hemorrhage was compared between the two groups. Among 4,439,778 pregnant women who gave birth during the study period, 168,940 (3.8%) were immigrant women. The odds of gestational diabetes mellitus (adjusted OR: 1.24; 95% CI: 1.21, 1.28), and cesarean section (adjusted OR: 1.26; 95% CI: 1.25–1.28)were higher in immigrant women than in Korean women, but the odds of preeclampsia (adjusted OR: 0.84; 95% CI: 0.81–0.86) and postpartum hemorrhage (adjusted OR 0.96, 95% CI 0.94–0.97) was lower in immigrant women than in Korean women. Immigrant women had different pregnancy outcomes. Pregnancy and postpartum management that reflects these characteristics will be necessary for immigrant women. [ABSTRACT FROM AUTHOR]

Pregnant women were excluded from vaccination against Coronavirus 2019 (COVID-19) until September 2021 in South Korea. Although vaccination for pregnant women started in October 2021, vaccine acceptance in pregnant women is yet unknown. This cross-sectional study aimed to investigate COVID-19 vaccine acceptance during pregnancy and influencing factors. An anonymous survey was distributed in obstetrics departments to all pregnant or postpartum women, during the prenatal or postpartum visit. The proportion of self-reported COVID-19 vaccination during pregnancy among 436 women was 26.6%. Pregnancy-related independent factors influencing maternal COVID-19 vaccination were "received vaccine information about from obstetrics and gynecology (OBGYN) doctors" (OR 3.41, 95% CI 2.05–5.65), "cohabitant COVID-19 vaccination" (OR 2.43, 95% CI 1.06–5.59), and "second trimester" (OR 7.35, 95% CI 1.54–35.15). In women who did not want to get vaccinated, the most common reason for COVID-19 vaccination hesitancy was concern that COVID-19 vaccine might affect the fetus (91.7%, 243/266), followed by distrust in COVID-19 vaccine effectiveness (42.6%, 113/266). This study showed that providing information about maternal COVID-19 vaccination, especially by OBGYN doctors, is crucial for increasing vaccination coverage in pregnant women. Providing updated evidence of COVID-19 vaccine efficacy and safety in pregnant women may be also helpful for increasing vaccine acceptance. [ABSTRACT FROM AUTHOR]

This study was a multicenter retrospective cohort study of term nulliparous women who underwent labor, and was conducted to develop an automated machine learning model for prediction of emergent cesarean section (CS) before onset of labor. Nine machine learning methods of logistic regression, random forest, Support Vector Machine (SVM), gradient boosting, extreme gradient boosting (XGBoost), light gradient boosting machine (LGBM), k-nearest neighbors (KNN), Voting, and Stacking were applied and compared for prediction of emergent CS during active labor. External validation was performed using a nationwide multicenter dataset for Korean fetal growth. A total of 6549 term nulliparous women was included in the analysis, and the emergent CS rate was 16.1%. The C-statistics values for KNN, Voting, XGBoost, Stacking, gradient boosting, random forest, LGBM, logistic regression, and SVM were 0.6, 0.69, 0.64, 0.59, 0.66, 0.68, 0.68, 0.7, and 0.69, respectively. The logistic regression model showed the best predictive performance with an accuracy of 0.78. The machine learning model identified nine significant variables of maternal age, height, weight at pre-pregnancy, pregnancy-associated hypertension, gestational age, and fetal sonographic findings. The C-statistic value for the logistic regression machine learning model in the external validation set (1391 term nulliparous women) was 0.69, with an overall accuracy of 0.68, a specificity of 0.83, and a sensitivity of 0.41. Machine learning algorithms with clinical and sonographic parameters at near term could be useful tools to predict individual risk of emergent CS during active labor in nulliparous women. [ABSTRACT FROM AUTHOR]

Background: Our objective was to evaluate risks of adverse obstetric outcomes in pregnancies with myoma(s) or in pregnancies following myomectomy.Methods: We analyzed the national health insurance database, which covers almost the entire Korean population, between 2004 and 2015. The risks of adverse pregnancy outcomes in pregnancies with myoma(s) or in pregnancies following myomectomy, compared to those in women without a diagnosed myoma, were analyzed in multivariate logistic regression analysis.Results: During the study period, 38,402 women with diagnosed myoma(s), 9890 women with a history of myomectomy, and 740,675 women without a diagnosed myoma gave birth. Women with a history of diagnosed myoma(s) and women with a history of myomectomy had significantly higher risks of cesarean section (aOR 1.13, 95% CI 1.1-1.16 and aOR 7.46, 95% CI 6.97-7.98, respectively) and placenta previa (aOR 1.41, 95% CI 1.29-1.54 and aOR 1.58, 95% CI 1.35-1.83, respectively), compared to women without a diagnosed myoma. And the risk of uterine rupture was significantly higher in women with previous myomectomy (aOR 12.78, 95% CI 6.5-25.13), compared to women without a diagnosed myoma, which was much increased (aOR 41.35, 95% CI 16.18-105.69) in nulliparous women. The incidence of uterine rupture was the highest at delivery within one year after myomectomy and decreased over time after myomectomy.Conclusions: Women with a history of myomectomy had significantly higher risks of cesarean section and placenta previa compared to women without a diagnosed myoma. [ABSTRACT FROM AUTHOR]