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Derivation and validation of a model predicting the likelihood of vaginal birth following labour induction.

ABSTRACT: BACKGROUND:There is high-quality evidence supporting induction of labour (IOL) for a number of maternal and fetal indications. However, one fifth of inductions fail to result in vaginal births, requiring cesarean deliveries. This has negative clinical, emotional and resource implications. The importance of predicting the success of labour induction to enable shared decision-making has been recognized, but existing models are limited in scope and generalizability. Our objective was to derive and internally validate a clinical prediction model that uses variables readily accessible through maternal demographic data, antenatal history, and cervical examination to predict the likelihood of vaginal birth following IOL. METHODS:Data was extracted from electronic medical records of consecutive pregnant women who were induced between April and December 2016, at Mount Sinai Hospital, Toronto, Canada. A multivariable logistic regression model was developed using 16 readily accessible variables identified through literature review and expert opinion, as predictors of vaginal birth after IOL. The final model was internally validated using 10-fold cross-validation. RESULTS:Of the 1123 cases of IOL, 290 (25.8%) resulted in a cesarean delivery. The multivariable logistic regression model found maternal age, parity, pre-pregnancy body mass index and weight, weight at delivery, and cervical dilation at time of induction as significant predictors of vaginal delivery following IOL. The prediction model was well calibrated (Hosmer-Lemeshow ?2?=?5.02, p?=?0.76) and demonstrated good discriminatory ability (area under the receiver operating characteristic (AUROC) curve, 0.81 (95% CI 0.78 to 0.83)). Finally, the model showed good internal validity [AUROC 0.77 (95% CI 0.73 to 0.82)]. CONCLUSIONS:We have derived and internally validated a well-performing clinical prediction model for IOL in a large and diverse population using variables readily accessible through maternal demographic data, antenatal history, and cervical examination. Once prospectively validated in diverse settings, and if shown to be acceptable to pregnant women and healthcare providers as well as clinically and cost-effective, this model has potential for widespread use in clinical practice and research for enhancing patient autonomy, improving induction outcomes, and optimizing allocation of resources.

SUBMITTER: Alavifard S

PROVIDER: S-EPMC6469110 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Derivation and validation of a model predicting the likelihood of vaginal birth following labour induction.

Alavifard Sepand S Meier Kennedy K Shulman Yonatan Y Tomlinson George G D'Souza Rohan R

BMC pregnancy and childbirth 20190416 1

<h4>Background</h4>There is high-quality evidence supporting induction of labour (IOL) for a number of maternal and fetal indications. However, one fifth of inductions fail to result in vaginal births, requiring cesarean deliveries. This has negative clinical, emotional and resource implications. The importance of predicting the success of labour induction to enable shared decision-making has been recognized, but existing models are limited in scope and generalizability. Our objective was to der ...[more]

PMID: 30991983

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Project description:PURPOSE: To determine the maternal and fetal outcomes of successful external cephalic version (ECV) as well as factors predicting vaginal birth. METHODS: The ECV data over a period of three years at Universiti Kebangsaan Malaysia Medical Centre (UKMMC) between 1 September 2008 and 30 September 2010 was reviewed. Sixty-seven patients who had successful ECV were studied and reviewed for maternal, fetal, and labour outcomes. The control group comprised patients with cephalic singletons of matching parity who delivered following the index cases. RESULTS: The mean gestational age at ECV was 263 ± 6.52 days (37.5 weeks ± 6.52 days). Spontaneous labour and transient cardiotocographic (CTG) changes were the commonest early adverse effects following ECV. The reversion rate was 7.46%. The mean gestational age at delivery of the two groups was significantly different (P = 0.000) with 277.9 ± 8.91 days and 269.9 ± 9.68 days in the study group and control groups, respectively. The study group needed significantly more inductions of labour. They required more operative deliveries, had more blood loss at delivery, a higher incidence of meconium-stained liquor, and more cord around the neck. Previous flexed breeches had a threefold increase in caesarean section rate compared to previous extended breeches (44.1% versus 15.2%, P = 0.010). On the contrary, an amniotic fluid index (AFI) of 13 or more is significantly associated with a higher rate of vaginal birth (86.8% versus 48.3%, P = 0.001). CONCLUSIONS: Patients with successful ECV were at higher risk of carrying the pregnancy beyond 40 weeks and needing induction of labour, with a higher rate of caesarean section and higher rates of obstetrics complications. Extended breech and AFI 13 or more were significantly more likely to deliver vaginally postsuccessful ECV. This additional information may be useful to caution a patient with breech that ECV does not bring them to behave exactly like a normal cephalic, so that they have more realistic expectations. However, these predictive factors needed further confirmation and hopefully, in the future, they would be able to further enhance counselling prior to ECV.

Project description:BackgroundProstaglandins have been used for induction of labour since the 1960s. This is one of a series of reviews evaluating methods of induction of labour. This review focuses on prostaglandins given per vaginam, evaluating these in comparison with placebo (or expectant management) and with each other; prostaglandins (PGE2 and PGF2a); different formulations (gels, tablets, pessaries) and doses.ObjectivesTo determine the effects of vaginal prostaglandins E2 and F2a for third trimester cervical ripening or induction of labour in comparison with placebo/no treatment or other vaginal prostaglandins (except misoprostol).Search methodsWe searched the Cochrane Pregnancy and Childbirth Group's Trials Register (1 March 2014) and bibliographies of relevant papers.Selection criteriaClinical trials comparing vaginal prostaglandins used for third trimester cervical ripening or labour induction with placebo/no treatment, with each other, or other methods listed above it on a predefined list of labour induction methods.Data collection and analysisWe assessed studies and extracted data independently.Main resultsSeventy randomised controlled trials (RCTs) (11,487 women) are included. In this update seven new RCTs (778 women) have been added. Two of these new trials compare PGE2 with no treatment, four compare different PGE2 formulations (gels versus tablets, or sustained release pessaries) and one trial compares PGF2a with placebo. The majority of trials were at unclear risk of bias for most domains.Overall, vaginal prostaglandin E2 compared with placebo or no treatment probably reduces the likelihood of vaginal delivery not being achieved within 24 hours. The risk of uterine hyperstimulation with fetal heart rate changes is increased (4.8% versus 1.0%, risk ratio (RR) 3.16, 95% confidence interval (CI) 1.67 to 5.98, 15 trials, 1359 women). The caesarean section rate is probably reduced by about 10% (13.5% versus 14.8%, RR 0.91, 95% CI 0.81 to 1.02, 36 trials, 6599 women). The overall effect on improving maternal and fetal outcomes (across a variety of measures) is uncertain.PGE2 tablets, gels and pessaries (including sustained release preparations) appear to be as effective as each other, small differences are detected between some outcomes, but these maybe due to chance.Authors' conclusionsProstaglandins PGE2 probably increase the chance of vaginal delivery in 24 hours, they increase uterine hyperstimulation with fetal heart changes but do not effect or may reduce caesarean section rates. They increase the likelihood of cervical change, with no increase in operative delivery rates. PGE2 tablets, gels and pessaries appear to be as effective as each other, any differences between formulations are marginal but may be important.

Project description:IntroductionA calculator estimating likelihood of vaginal birth after cesarean (VBAC) has been promoted by the Society for Maternal-Fetal Medicine, but little is known about how it is used and perceived in practice. Cutoffs for prohibiting labor after cesarean are discouraged by the calculator's developers, but such uses may be widespread. The purpose of this study was to determine how calculators predicting VBAC are used and perceived in midwifery practices.MethodsCertified nurse-midwives and certified midwives currently providing care for labor after cesarean were surveyed between January 17, 2019, and February 7, 2019. Quantitative and text data were collected regarding the uses and perceptions of calculators among midwives and their colleagues. We compared these findings with midwives' perceptions of their ability to accommodate patient wishes for labor after cesarean. We used descriptive content analysis to evaluate themes occurring in text responses.ResultsThere were 1305 valid responses. A requirement to use calculator scores for patient counseling was reported by 527 (40.4%) of responding midwives. Over 1 in 5 midwives reported that scores were used to discourage or prohibit labor after cesarean. Almost half reported some or strong disagreement with physician colleagues regarding calculator use. Interprofessional agreement and disagreement centered on how scores are used to direct clinical care or restrict patient options. Calculator scores were used in more than twice as many midwives' practices to discourage rather than encourage labor after cesarean. Descriptive analysis of text revealed 4 themes regarding calculators: inconsistent use, information counseling, informed consent, and influence patient management or options.DiscussionCalculators predicting likelihood of VBAC success are widely used in midwifery settings and are more often used to discourage than to encourage labor after cesarean. Midwives reported both directive and nondirective counseling based on calculator scores.

Project description:An association between the vaginal microbiome and preterm birth has been reported. However, in practice, it is difficult to predict premature birth using the microbiome because the vaginal microbial community varies highly among samples depending on the individual, and the prediction rate is very low. The purpose of this study was to select markers that improve predictive power through machine learning among various vaginal microbiota and develop a prediction algorithm with better predictive power that combines clinical information. As a multicenter case-control study with 150 Korean pregnant women with 54 preterm delivery group and 96 full-term delivery group, cervicovaginal fluid was collected from pregnant women during mid-pregnancy. Their demographic profiles (age, BMI, education level, and PTB history), white blood cell count, and cervical length were recorded, and the microbiome profiles of the cervicovaginal fluid were analyzed. The subjects were randomly divided into a training (n = 101) and a test set (n = 49) in a two-to-one ratio. When training ML models using selected markers, five-fold cross-validation was performed on the training set. A univariate analysis was performed to select markers using seven statistical tests, including the Wilcoxon rank-sum test. Using the selected markers, including Lactobacillus spp., Gardnerella vaginalis, Ureaplasma parvum, Atopobium vaginae, Prevotella timonensis, and Peptoniphilus grossensis, machine learning models (logistic regression, random forest, extreme gradient boosting, support vector machine, and GUIDE) were used to build prediction models. The test area under the curve of the logistic regression model was 0.72 when it was trained with the 17 selected markers. When analyzed by combining white blood cell count and cervical length with the seven vaginal microbiome markers, the random forest model showed the highest test area under the curve of 0.84. The GUIDE, the single tree model, provided a more reasonable biological interpretation, using the 10 selected markers (A. vaginae, G. vaginalis, Lactobacillus crispatus, Lactobacillus fornicalis, Lactobacillus gasseri, Lactobacillus iners, Lactobacillus jensenii, Peptoniphilus grossensis, P. timonensis, and U. parvum), and the covariates produced a tree with a test area under the curve of 0.77. It was confirmed that the association with preterm birth increased when P. timonensis and U. parvum increased (AUC = 0.77), which could also be explained by the fact that as the number of Peptoniphilus lacrimalis increased, the association with preterm birth was high (AUC = 0.77). Our study demonstrates that several candidate bacteria could be used as potential predictors for preterm birth, and that the predictive rate can be increased through a machine learning model employing a combination of cervical length and white blood cell count information.

Project description:IntroductionPostpartum hemorrhage (PPH) is an important contributor to maternal morbidity and mortality. Predicting which laboring women are likely to have a PPH is an active area of research and a component of quality improvement bundles. The purpose of this study was to identify phenotypes of labor processes (ie, labors that have similar features, such as duration and type of interventions) in a cohort of women who had vaginal births, estimate the likelihood of PPH by phenotype, and analyze how maternal and fetal characteristics relate to PPH risk by phenotype.MethodsThis study utilized the Consortium for Safe Labor dataset (2002-2008) and examined term, singleton, vaginal births. Using 16 variables describing the labor and birth processes, a latent class analysis was performed to describe distinct labor process phenotypes.ResultsOf 24,729 births, 1167 (4.72%) women experienced PPH. Five phenotypes best fit the data, reflecting labor interventions, duration, and complications. Women who had shorter duration of admission after spontaneous labor onset (admitted in latent or active labor) had the lowest rate of PPH (3.8%-3.9%). The 2 phenotypes of labor progress characterized by women who had complicated prolonged labors (spontaneous or induced) had the highest rate of PPH (8.0% and 12.0%, respectively). However, the majority of PPH (n = 881, 75%) occurred in the phenotypes with fewer complications. Prepregnancy body mass index did not predict PPH. Overall, the odds of PPH were highest among nulliparous women (odds ratio [OR], 1.52; 95% CI, 1.30-1.77), as well as Black women (OR, 1.39; 95% CI, 1.13-1.73) and Hispanic women (OR, 1.85; 95% CI, 1.56-2.20). Within phenotypes, maternal race and ethnicity, nulliparity, macrosomia, hypertension, and depression were associated with increased odds of PPH.DiscussionWomen who were classified into a lower-risk labor phenotype and still experienced PPH were more likely to be nulliparous, a person of color, or diagnosed with hypertension.

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Derivation and validation of a model predicting the likelihood of vaginal birth following labour induction.

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Derivation and validation of a model predicting the likelihood of vaginal birth following labour induction.

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