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Should Plain X-rays be Routinely Performed After Blunt Knee Trauma? A Prospective Analysis

2005· article· en· W2046465324 on OpenAlexaboutno aff
Jean–Yves Jenny, Cyril Boéri, H. El Amrani, J.-C. Dosch, Michel Dupuis, A. Moussaouï, Fabrice Mairot

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2005
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBlunt traumaStage (stratigraphy)BluntSurgeryFracture (geology)Materials science

Abstract

fetched live from OpenAlex

BACKGROUND: We tested the hypothesis that it was possible to decrease the number of performed x-rays after a knee trauma without delayed fracture diagnosis by using the Ottawa knee rules. METHODS: Patients had routine x-rays of the injured knee during the first stage of the study and selective x-rays during the second stage. All patients were followed up to 6 months after the trauma. RESULTS: 138 patients were included in the first stage; 57 had negative Ottawa criteria: no fracture was observed; following the Ottawa rules, 41% of the x-rays could have been avoided. 178 patients were included in the second stage; 63 patients had negative Ottawa criteria: no fracture was diagnosed during the whole follow-up; 35% of the x-rays have been avoided. CONCLUSIONS: Ottawa rules allowed decreasing the number of x-rays performed after a knee trauma by 35% with a sensitivity for a knee fracture detection of 100%.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.316
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Trauma: Injury, Infection, and Critical CareSame topicKnee injuries and reconstruction techniquesFrench-language works237,207