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A comparison of prilocaine and lidocaine for intravenous regional anaesthesia for forearm fracture reduction in children

2002· article· en· W2075014651 on OpenAlexaff
Andrew Davidson, Robert L. Eyres, William G. Cole

Bibliographic record

VenuePediatric Anesthesia · 2002
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicinePrilocaineLidocaineAnesthesiaForearmReduction (mathematics)SurgeryFracture reductionIntravenous regional anesthesiaInternal fixation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.279
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2002
Admission routes1
Has abstractyes

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