Outpatient Cervical Ripening: A Multicentered Retrospective Cohort Study [ID: 1377444]
Bibliographic record
Abstract
INTRODUCTION: This study aims to compare safety and effectiveness between different outpatient cervical ripening (CR) methods. METHODS: Seven community and academic hospitals in the Greater Toronto Area that performed outpatient CR participated. We reviewed eligible charts over 12–24 months based on predetermined criteria. Multivariable analyses were performed; covariates included nulliparity, cervical unfavourability, and maternal and gestational age. Binary outcomes were modeled using logistic regression, presented as adjusted odds ratio (OR) with 95% CI. Time-to-event outcomes were described using unadjusted Kaplan-Meier curves. Multivariable time-to-event analyses were performed using accelerated failure time models with effects presented as time ratios (TRs) with 95% CI. RESULTS: We identified 1,910 pregnancies that underwent outpatient CR using balloon catheters in 881 (46%), dinoprostone vaginal inserts (DVIs) in 553 (29%), and dinoprostone vaginal gel/tablets (DG/T) in 476 (25%) pregnancies. The choice of agent varied considerably per site; one site used balloon catheters in 95%, another used DG/T in 95%, and three sites used DVI in more than 74% of cases. There were no differences in cesarean deliveries or adverse events related to CR. Compared to balloon catheters, patients with pharmacological ripening more often needed a subsequent ripening agent (DVI adjusted odds ratio 2.32 [1.62, 2.81], DG/T 3.26 [2.44, 4.36]). CR-to-delivery time did not differ, but compared to balloon catheters, DG/T had a shorter admission-to-delivery (aTR 0.71 [0.59, 0.86]) interval. CONCLUSION: Balloon catheters, DVI, and DG/T for outpatient CR are comparable in terms of safety and effectiveness. When choosing between agents, consideration should be given to clinical findings, patient preference, and resource availability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".