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The Bernese Ankle Rules: A Fast, Reliable Test after Low-Energy, Supination-Type Malleolar and Midfoot Trauma

2005· article· en· W1967268402 on OpenAlexaboutno aff
Stefan Eggli, Guido M. Sclabas, Simone Eggli, Heinz Zimmermann, Aristomenis K. Exadaktylos

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2005
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsAnkleMedicinePalpationAnkle injuryPhysical examinationRadiographyReduction (mathematics)WeaknessSurgeryPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Trauma of the midfoot and ankle joint are among the most commonly treated injuries in the emergency unit. The "Ottawa ankle rules" were introduced in 1992 to lower the amount of radiographs based on a standardized clinical examination. The weakness of the "rules" is the low specificity reported in several clinical studies. METHOD: We introduced a new indirect stress technique to examine the ankle and the midfoot after low-energy, supination-type trauma, avoiding direct palpation of the injured region. RESULTS: In 354 prospectively documented patients, the Bernese ankle test produced a sensitivity of 100% and a specificity of 91%. CONCLUSION: Compared with the original Ottawa ankle rules, the number of false-positive findings could be significantly reduced, resulting in a reduction of 84% in radiographs after low-energy, supination-type trauma ankle and midfoot trauma. Further investigations have to be performed to prove whether these findings are reproducible within other clinical settings, which could result in major cost savings for the health care system.

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 score0.364
Threshold uncertainty score0.441

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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations29
Published2005
Admission routes1
Has abstractyes

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