Epidural Ropivacaine Versus Bupivacaine for Labor: A Meta-Analysis
Bibliographic record
Abstract
UNLABELLED: Numerous studies have compared ropivacaine with bupivacaine for labor analgesia. Early studies suggested that obstetrical and some neonatal outcomes were improved when ropivacaine was used. We systematically reviewed and combined the results of the randomized controlled trials that compared ropivacaine with bupivacaine to determine whether or not there was a difference in these outcomes. We searched electronic databases and journals for randomized controlled trials composed of laboring parturients. The primary outcome was the incidence of spontaneous vaginal delivery. We examined other obstetrical, neonatal, and analgesic outcomes. Where possible, these were combined by using metaanalytic techniques and random effects modeling. We found 23 randomized controlled trials composed of 1043 patients receiving ropivacaine and 1031 receiving bupivacaine. There was no significant difference in the incidence of spontaneous vaginal delivery (odds ratio, 1.17; 95% confidence interval, 0.98-1.41; P = 0.12) or any of the other outcomes. Although more studies reported a more frequent incidence of motor block with bupivacaine, the results were heterogeneous and therefore not combined. We conclude that there is no statistically significant difference between the two drugs in the incidence of any obstetrical or neonatal outcome. Further studies using clinically appropriate concentrations of drugs are required to determine whether or not there is a difference in the incidence of motor block. IMPLICATIONS: This metaanalysis of 23 randomized controlled trials shows that both ropivacaine and bupivacaine provide excellent labor analgesia. There was no significant difference between the two drugs in mode of delivery, maternal satisfaction, or neonatal outcomes. Whether or not there is a difference in motor block at clinically relevant doses is unresolved.
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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 | 0.024 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.054 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".