Uterotonics in Elective Caesarean Delivery: A Randomised Noninferiority Study Comparing Carbetocin 20 and 100 µg
Bibliographic record
Abstract
(Anaesthesia. 2019;74:190–196) Postpartum hemorrhage (PPH) is the most common cause of maternal mortality worldwide and accounts for 35% of maternal deaths. Active management of the third stage of labor is recommended in all parturients, with prophylactic uterotonic drug administration after delivery of the infant being the primary component of this active management. This strategy alone has been shown to decrease the incidence of PPH by up to 40%. The 2009 guidelines from the Society of Obstetricians and Gynaecologists of Canada (SOGC) recommended a single 100 µg intravenous bolus dose of carbetocin as the uterotonic agent of choice, rather than an oxytocin infusion, to prevent PPH after elective cesarean delivery. The rationale for recommending this dose was based on the manufacturer’s recommendation and some clinical trials. Some more recent studies, however, have suggested that doses as low as 15 µg may be effective at preventing PPH after elective cesarean delivery. The current investigators believed a larger trial comparing this smaller dose with the standard 100 µg dose was warranted to confirm these findings. This study was undertaken to compare the uterine tone intensity achieved with 20 carbetocin versus 100 µg carbetocin in women at low risk of PPH undergoing elective cesarean delivery under spinal anesthesia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".