Oxytocin at elective caesarean delivery: a dose‐finding study in women with obesity
Bibliographic record
Abstract
Summary Prophylactic oxytocin administration at the third stage of labour reduces blood loss and the need for additional uterotonic drugs. Obesity is known to be associated with an increased risk of uterine atony and postpartum haemorrhage. It is unknown whether women with obesity require higher doses of oxytocin in order to achieve adequate uterine tone after delivery. The purpose of this study was to establish the bolus dose of oxytocin required to initiate effective uterine contraction in 90% of women with obesity (the ED 90 ) at elective caesarean delivery. We conducted a double‐blind dose‐finding study using the biased coin up‐down design method. Term pregnant women with a BMI ≥ 40 kg.m −2 undergoing elective caesarean delivery under regional anaesthesia were included. Those with conditions predisposing to postpartum haemorrhage were not included. Oxytocin was administered as an intravenous bolus over 1 minute upon delivery of the fetus. With the first woman receiving 0.5 IU, oxytocin doses were administered according to a sequential allocation scheme. The primary outcome measure was satisfactory uterine tone, as assessed by the operating obstetrician 2 minutes after administration of the oxytocin bolus. Secondary outcomes included the need for rescue uterotonic drugs, adverse effects and estimated blood loss. We studied 30 women with a mean (SD) BMI of 52.3 (7.6) kg.m ‐2 . The ED 90 for oxytocin was 0.75 IU (95%CI 0.5–0.93 IU) by isotonic regression and 0.78 IU (95%CI 0.68–0.88 IU) by the Dixon and Mood method. Our results suggest that women with a BMI ≥ 40 kg.m ‐2 require approximately twice as much oxytocin as those with a BMI < 40 kg.m ‐2 , in whom an ED 90 of 0.35 IU (95%CI 0.15–0.52 IU) has previously been demonstrated.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".