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

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 χ2 = 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.

Research Productivity and Rankings of Anesthesiology Departments in Canada and the United States: The Relationship Between the h-Index and Other Common Metrics [RETRACTED].

BACKGROUND: To evaluate the relative research productivity and ranking of anesthesiology departments in Canada and the United States, using the Hirsch index (h-index) and 4 other previously validated metrics. METHODS: We identified 150 anesthesiology departments in Canada and the United States with an accredited residency program. Publications for each of the 150 departments were identified using Thomson's Institute for Scientific Information Web of Science, and the citation report for each department was exported. The bibliometric data were used to calculate publication metrics for 3 time periods: cumulative (1945-2014), 10 years (2005-2014), and 5 years (2010-2014). The following group metrics were then used to determine the publication impact and relative ranking of all 150 departments: h-index, m-index, total number of publications, sum of citations, and average number of citations per article. Ranking for each metric were also stratified by using a proxy for departmental size. The most common journals in which US and Canadian anesthesiology departments publish their work were identified. RESULTS: The majority (23 of the top 25) of top-ranked anesthesiology departments are in the United States, and 2 of the top 25 departments (University of Toronto; McGill University) are in Canada. There was a strong positive relationship between each of h-index, total number of publications, and the sum of citations (0.91-0.97; P < .0001). Departmental size correlates with increased academic productivity on most metrics. The most frequent journals in which US and Canadian anesthesiology departments publish are Anesthesiology, Anesthesia and Analgesia, and the Canadian Journal of Anesthesia. CONCLUSIONS: Our study ranked the Canadian and US anesthesiology departmental research productivity using the h-index applied to each department, total number of publications, total number of citations, and average number of citations. The strong relationship between the h-index and both the number of publications and number of citations of anesthesiology departments shows that the departments with the highest number of publications are also producing research with the most highly cited articles (ie, most impact), as demonstrated by the h-index.

Inter-rater reliability of h-index scores calculated by Web of Science and Scopus for clinical epidemiology scientists.

OBJECTIVE: We investigated the inter-rater reliability of Web of Science (WoS) and Scopus when calculating the h-index of 25 senior scientists in the Clinical Epidemiology Program of the Ottawa Hospital Research Institute. MATERIALS AND METHODS: Bibliometric information and the h-indices for the subjects were computed by four raters using the automatic calculators in WoS and Scopus. Correlation and agreement between ratings was assessed using Spearman's correlation coefficient and a Bland-Altman plot, respectively. RESULTS: Data could not be gathered from Google Scholar due to feasibility constraints. The Spearman's rank correlation between the h-index of scientists calculated with WoS was 0.81 (95% CI 0.72-0.92) and with Scopus was 0.95 (95% CI 0.92-0.99). The Bland-Altman plot showed no significant rater bias in WoS and Scopus; however, the agreement between ratings is higher in Scopus compared to WoS. CONCLUSION: Our results showed a stronger relationship and increased agreement between raters when calculating the h-index of a scientist using Scopus compared to WoS. The higher inter-rater reliability and simple user interface used in Scopus may render it the more effective database when calculating the h-index of senior scientists in epidemiology.

Neurocognitive outcomes following fetal exposure to chemotherapy for gestational breast cancer: A Canadian multi-center cohort study.

BACKGROUND: Limited knowledge exists on outcomes of children exposed prenatally to chemotherapy for breast cancer (BC). The purpose of this study was to compare long-term neurocognitive, behavioral, developmental, growth, and health outcomes of children exposed in-utero to chemotherapy for BC. METHODS: This is a multi-center matched cross-sectional cohort study involving seven cancer centers across the region of Southern Ontario (Canada), and the Hospital for Sick Children (Toronto, Ontario). Using standardized psychological and behavioral tests, we compared cognitive and behavioral outcomes in children exposed to chemotherapy during pregnancy for BC to age-matched pairs exposed to known non-teratogens. RESULTS: We recruited 17 parent-child pairs and their matched controls. There were more preterm deliveries in the chemotherapy-exposed group compared to controls (p < 0.05). Full Scale IQ of children in the chemotherapy group was significantly confounded by maternal IQ and prematurity. Exposed children born at term were not different in cognitive outcomes. Children from both groups were similar in their developmental milestones, pediatric anthropometric measurements and health problems. There were no cases of autoimmune cytopenia. CONCLUSIONS: This is the first Canadian prospective comparative study designed to assess pediatric cognition following prenatal exposure to chemotherapy for BC. Chemotherapy was not found to be neurotoxic in this cohort and did not affect pediatric health. The decision to plan a preterm birth for initiating or continuing chemotherapy treatment must be taken into consideration in context of pediatric implications. While these results may assist in such decision making, replication with a larger sample is needed for more conclusive findings.

First-line antihypertensive treatment for severe hypertension in pregnancy: A systematic review and network meta-analysis.

BACKGROUND: Hydralazine, labetalol, and nifedipine are the recommended first-line treatments for severe hypertension in pregnancy. While all three are effective, there is a lack of sufficient evidence regarding their comparative safety and efficacy. OBJECTIVE: To determine the comparative safety and efficacy of the first-line treatment options for severe hypertension in pregnancy. METHODS: A systematic search of Medline, Embase, and Cochrane Central Register of Controlled Trials up to May 31, 2018 was conducted. RCTs in pregnancy comparing a first-line antihypertensive agent to another first-line agent for the treatment of severe hypertension in pregnancy. Screening, data abstraction, and quality assessment were done by two independent reviewers. To estimate relative effects from all available evidence, a Bayesian network meta-analysis with vague priors was conducted. MAIN RESULTS: Of the 1330 publications identified, 17 RCTs comprised of a total of 1591 women met our selection criteria. For successful treatment of severe hypertension, nifedipine was found to be superior to hydralazine (OR 4.13 [95% CrI 1.01-20.75]) but not labetalol (OR 3.43 [95% CrI 0.94-19.95]). This was not associated with an increased risk for caesarean delivery or maternal side effects. There was no significant difference between labetalol and hydralazine. CONCLUSIONS: Given the results of this systematic review and network meta-analysis, maternity care providers should feel comfortable initiating management of severe hypertension in pregnancy using oral nifedipine.