Determination of the optimal programmed intermittent epidural bolus volume of bupivacaine 0.0625% with fentanyl 2 μg.ml <sup>−1</sup> at a fixed interval of forty minutes: a biased coin up‐and‐down sequential allocation trial
Bibliographic record
Abstract
Summary The optimum time interval for 10 ml boluses of bupivacaine 0.0625% + fentanyl 2 μg.ml −1 as part of a programmed intermittent epidural bolus regimen has been found to be 40 min. This regimen was shown to be effective without the use of supplementary patient‐controlled epidural analgesia boluses in 90% of women during the first stage of labour, although with a rate of sensory block to ice above T6 in 34% of women. We aimed to determine the optimum programmed intermittent epidural bolus volume at a 40 min interval to provide effective analgesia in 90% of women ( EV 90 ) during the first stage of labour, without the use of patient‐controlled epidural analgesia. We performed a prospective double‐blind dose‐finding study using the biased coin up‐and‐down sequential allocation method in 40 women. The estimated EV 90 was 11.0 (95% CI 10.0–11.7) ml with the isotonic regression method and 10.7 (95% CI 10.3–11.0) ml with the truncated Dixon and Mood method. Overall, 18 women had a sensory block above T6, and 37 women exhibited no motor block. No women required treatment for hypotension. In conclusion, it is not possible to reduce the programmed intermittent epidural bolus volume from 10 ml, used in our current regimen, without compromising the quality of analgesia. Using this regimen, a high proportion of women will develop a sensory block above T6.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".