Artificial rupture of membranes as a mode for induction of labor in women with a previous cesarean section- a retrospective cohort study.

BACKGROUND: Induction of labor in women with a previous cesarean section (CS) is associated with increased rates of uterine rupture and failed attempt for vaginal delivery. Prostaglandins use is contraindicated in this population, limiting available options for cervical ripening. OBJECTIVE: To evaluate the efficacy and safety of artificial rupture of membranes (AROM) as a mode of Induction of labor (IOL) in women with a previous cesarean section. METHODS: A retrospective cohort study conducted in a single tertiary care center between January 2015 and October 2020. Women with one previous cesarean section and a current singleton term pregnancy requiring IOL, with an unfavorable cervix, were included. The primary outcome was a successful vaginal delivery (VBAC); secondary outcomes were rates of chorioamnionitis, uterine rupture and low Apgar score (< 7). RESULTS: Of the 665 women who met the inclusion criteria, 492 (74%) did not receive subsequent oxytocin and 173 (26%) did. There were significant differences in the baseline characteristics between these two groups, including maternal age, cervical dilation at presentation, parity, and a history of a previous VBAC. Among women who were induced solely by AROM the rate of a successful TOLAC was higher (81.3% vs 73.9%), total time of IOL was shorter (mean 8.7 h vs.16.1 h) and the risk of chorioamnionitis was lower (7.3% vs 18.4%). When subdividing the women who received oxytocin into early (< 12 h after AROM) vs late (> 12 h after AROM) administration, there were no significant changes in the rates of successful VBAC or of chorioamnionitis. CONCLUSION: AROM as a single mode of IOL in women with a previous CS is a safe and efficient practice with high rates of successful VBAC. When spontaneous labor does not develop, there is no advantage to delay the administration of oxytocin.

Prediction model for obstetric anal sphincter injury using machine learning.

INTRODUCTION AND HYPOTHESIS: Obstetric anal sphincter injury (OASI) is a complication with substantial maternal morbidity. The aim of this study was to develop a machine learning model that would allow a personalized prediction algorithm for OASI, based on maternal and fetal variables collected at admission to labor. MATERIALS AND METHODS: We performed a retrospective cohort study at a tertiary university hospital. Included were term deliveries (live, singleton, vertex). A comparison was made between women diagnosed with OASI and those without such injury. For formation of a machine learning-based model, a gradient boosting machine learning algorithm was implemented. Evaluation of the performance model was achieved using the area under the receiver-operating characteristic curve (AUC). RESULTS: Our cohort comprised 98,463 deliveries, of which 323 (0.3%) were diagnosed with OASI. Applying a machine learning model to data recorded during admission to labor allowed for individualized risk assessment with an AUC of 0.756 (95% CI 0.732-0.780). According to this model, a lower number of previous births, fewer pregnancies, decreased maternal weight and advanced gestational week elevated the risk for OASI. With regard to parity, women with one previous delivery had approximately 1/3 of the risk for OASI compared to nulliparous women (OR = 0.3 (0.23-0.39), p < 0.001), and women with two previous deliveries had 1/3 of the risk compared to women with one previous delivery (OR = 0.35 (0.21-0.60), p < 0.001). CONCLUSION: Our machine learning-based model stratified births to high or low risk for OASI, making it an applicable tool for personalized decision-making upon admission to labor.

Growth pattern of uterine leiomyoma along pregnancy.

BACKGROUND: Uterine leiomyomas are often discovered during early pregnancy and in most cases will have no effect on pregnancy outcomes. However, in rare cases uterine leiomyomas may lead to obstetric complications. The aim of the study was to evaluate rate of uterine leiomyoma growth in the 3 trimesters of pregnancy. METHODS: We conducted a retrospective cohort study. Included were women who were diagnosed with uterine leiomyoma during pregnancy and had at least two sonographic measurements in different trimesters. Data regarding leiomyoma growth, recorded by ultrasound examination, during 1st 2nd and 3rd trimesters were collected from electronic patient records. RESULTS: Two-hundred forty-eight uterine leiomyomas were included in the study. Leiomyoma area increased substantially in size between the 1st and 2nd trimesters (54.5% ± 75.9%, p = .007) and to a lesser degree between the 2nd and 3rd trimesters (17.9% ± 59.7%, NS). Evaluation of the change in size throughout the pregnancy - between 1st and 3rd trimesters revealed a significant increase of 95.9% ± 191.3% (p < .001). There was no significant growth of the leiomyomas between the 2nd and 3rd trimesters. CONCLUSIONS: Uterine leiomyomas tend to grow substantially during the 1st trimester of pregnancy. This trend is attenuated later with minimal growth towards the end of gestation.