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Record W2090917349 · doi:10.1097/bot.0b013e3182454ff8

A Comparison of Pediatric Forearm Fracture Reduction Between Conscious Sedation and General Anesthesia

2012· article· en· W2090917349 on OpenAlexaff
Paul McKenna, Mike Leonard, Paul Connolly, S. Boran, Damian McCormack

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2012
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsMedicineSedationForearmAnesthesiaReduction (mathematics)Fracture reductionSurgeryRadiography

Abstract

fetched live from OpenAlex

OBJECTIVES: The purpose of this study was to compare the outcomes of children whose fractures were manipulated with nitrous oxide with those fractures manipulated under a general anesthetic. DESIGN: We undertook a retrospective analysis of all children who presented to the emergency department with an angulated or displaced nonphyseal forearm fracture requiring manipulation over a 6-month period. PATIENTS/PARTICIPANTS: Twenty-eight forearm fractures were manipulated using conscious sedation, whereas 27 were manipulated in the operating theatre under general anesthesia. MAIN OUTCOME MEASUREMENTS: The quality of reduction, the Cast Index, Padding Index, and Canterbury Index were similar between the 2 groups. RESULTS: There was a significant difference between the need for remanipulation in the nitrous oxide group (9) compared with the need for remanipulation in the theatre group (3). CONCLUSIONS: Despite a higher failure, manipulation of fractures in the emergency department using conscious sedation can achieve an adequate reduction and a high quality of cast. Failures were due to inherently more unstable fracture personalities. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

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)0.001
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 score0.154
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.080
GPT teacher head0.360
Teacher spread0.280 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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