Chorioamnionitis at latent phase more than doubles the risk for cesarean delivery compared to chorioamnionitis at active phase

Rottenstreich, Amihai; Tsur, Abraham; Shai, Daniel; Meyer, Raanan

doi:10.1007/s00404-020-05815-9

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…Intrauterine infection may cause fever, increased fetal heart rate, uterine inertia, and fetal distress, thus increasing the risk of cesarean section. 19 Premature rupture of the membrane leads to the reduction of amniotic fluid, which is harmful for the fetal head rotation at delivery. Under this condition, the umbilical cord is susceptible to be compressed.…”

Section: Discussionmentioning

confidence: 99%

Establishment and Validation of a Machine Learning-Based Prediction Model for Termination of Pregnancy via Cesarean Section

Zhang,

Sheng,

Liu

et al. 2023

IJGM

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Objective This study aimed to investigate the risk factors of cesarean section and establish a prediction model for cesarean section based on the characteristics of pregnant women. Methods The clinical characteristics of 2552 singleton pregnant women who delivered a live baby between January 2020 and December 2021 were retrospectively reviewed. They were divided into vaginal delivery group (n = 1850) and cesarean section group (n = 702). These subjects were divided into training set (2020.1–2021.6) and validation set (2021.7–2021.12). In the training set, univariate analysis, Lasso regression, and Boruta were used to screen independent risk factors for cesarean section. Four models, including Logistic Regression (LR), K-Nearest Neighbor (KNN), Classification and Regression Tree (CART), and Random forest (RF), were established in the training set using K-fold cross validation, hyperparameter optimization, and random oversampling techniques. The best model was screened, and Sort graph of feature variables, univariate partial dependency profile, and Break Down profile were delineated. In the validation set, the confusion matrix parameters were calculated, and receiver operating characteristic curve (ROC), precision recall curve (PRC), calibration curve, and clinical decision curve analysis (DCA) were delineated. Results The risk factors of cesarean section included age and height of women, weight at delivery, weight gain, para, assisted reproduction, abnormal blood glucose during pregnancy, pregnancy hypertension, scarred uterus, premature rupture of membrane (PROM), placenta previa, fetal malposition, thrombocytopenia, floating fetal head, and labor analgesia. RF had the best performance among the four models, and the accuracy of confusion matrix parameters was 0.8956357. The Matthews correlation coefficient (MCC) was 0.753012. The area under ROC (AUC-ROC) was 0.9790787, and the area under PRC (AUC-PRC) was 0.957888. Conclusion RF prediction model for caesarean section has high discrimination performance, accuracy and consistency, and outstanding generalization ability.

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Section: Discussionmentioning

confidence: 99%

Establishment and Validation of a Machine Learning-Based Prediction Model for Termination of Pregnancy via Cesarean Section

Zhang,

Sheng,

Liu

et al. 2023

IJGM

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“…The role of cervical polypectomy during pregnancy is still debated. It has been reported that the polypectomy during pregnancy significantly reduces the incidence of chorioamnionitis compared to women in which the polypectomy was delayed until delivery [ 12 , 15 ]. Based on this scenario, some studies recommend the resection of cervical polyps for pregnant women with clinical symptoms (i.e., active genital bleeding or vaginal discharge).…”

Section: Introductionmentioning

confidence: 99%

Surgical management of endocervical and decidual polyps during pregnancy: systematic review and meta-analysis

Riemma

Corte

Vitale

et al. 2022

Arch Gynecol Obstet

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Purpose To evaluate the impact of endocervical and decidual polypectomy on obstetrical outcomes of pregnant women. Methods MEDLINE, Scopus, ClinicalTrials.gov, Scielo, EMBASE, Cochrane Library at the CENTRAL Register of Controlled Trials, and LILACS were searched from inception to April 2021. No language or geographical restrictions were applied. Inclusion criteria regarded observational studies concerning pregnant women with a cervical lesion who underwent cervical polypectomy. Co-primary outcomes were incidence of late pregnancy loss and preterm birth in women with endocervical or decidual polypectomy as well as polypectomy versus expectant management. Random effect meta-analyses to calculate risk ratio (RR) with 95% confidence interval (CI) were performed. Quality assessment of included papers was performed using Newcastle–Ottawa Scale criteria. Results Three studies, with data provided for 3097 women, were included in quantitative analysis, with comparisons between endocervical and decidual polyps extracted from two studies and 156 patients. After a first trimester endocervical or decidual polypectomy, no significant differences were found for late pregnancy losses (RR 0.29 [95% CI 0.05, 1.80], I2 = 11%). Risk for preterm birth was significantly higher for decidual polyps’ removal (RR 6.13 [95% CI 2.57, 14.59], I2 = 0%). One paper compared cervical polypectomy vs expectant management, with increased incidence of late pregnancy loss (4/142 vs 5/2799; p < 0.001) and preterm birth (19/142 vs 115/2799; p < 0.001) in women subjected to polypectomy. Conclusions Evidence regarding the removal of cervical polyps in pregnancy is extremely limited. However, the removal of either decidual or endocervical polyps seems associated with increased risk of pregnancy loss and preterm birth, with increased preterm birth risk following endocervical rather than decidual polypectomy.

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The latent phase of labor

Cohen¹,

Friedman²

2023

American Journal of Obstetrics and Gynecology

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Chorioamnionitis at latent phase more than doubles the risk for cesarean delivery compared to chorioamnionitis at active phase

Cited by 5 publications

References 14 publications

Establishment and Validation of a Machine Learning-Based Prediction Model for Termination of Pregnancy via Cesarean Section

Establishment and Validation of a Machine Learning-Based Prediction Model for Termination of Pregnancy via Cesarean Section

Surgical management of endocervical and decidual polyps during pregnancy: systematic review and meta-analysis

The latent phase of labor

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