A comparison of prilocaine and lidocaine for intravenous regional anaesthesia for forearm fracture reduction in children
Bibliographic record
Abstract
BACKGROUND: In this prospective blinded randomized study, we compared prilocaine and lidocaine for intravenous regional anaesthesia for forearm fracture reduction in children. METHODS: Two hundred and seventy-nine children, aged 316 years, were enrolled and randomly assigned to receive 3 mg.kg-1 of either prilocaine or lidocaine. The severity of fracture was classified according to the displacement of the radius (i.e., no radial fracture, angulated, partly displaced or completely displaced). Pain during the procedure was assessed as none, minimal, moderate or severe. RESULTS: There was no significant difference between agents in the proportion of patients with a successful reduction (prilocaine 94%, lidocaine 92%). Compared with less severe fractures, successful reduction was less common in the completely displaced fractures (P < 0.001) but there was no significant difference in this category between anaesthetic agents (successful reduction: prilocaine, 84%; lidocaine, 78%). Analgesia was superior in the lidocaine group with more patients having no or minimal pain (prilocaine, 78%; lidocaine, 90%, P < 0.05). CONCLUSIONS: Both agents are effective for forearm fracture reduction in children with a high incidence of successful reductions, particularly in the minimally or nondisplaced fractures. Lidocaine provided superior analgesia.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| 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".