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Record W2265634151 · doi:10.1123/jsr.2014-0253

Validation of the Ottawa Ankle Rules for Acute Foot and Ankle Injuries

2015· article· en· W2265634151 on OpenAlexaboutno aff
Shannon David, Kim Gray, Jeffrey A. Russell, Chad Starkey

Bibliographic record

VenueJournal of Sport Rehabilitation · 2015
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiographyAnkleContingency tablePhysical therapyFalse positive paradoxAnkle injuryRadiologySurgeryStatistics

Abstract

fetched live from OpenAlex

UNLABELLED: The original and modified Ottawa Ankle Rules (OARs) were developed as clinical decision rules for use in emergency departments. However, the OARs have not been evaluated as an acute clinical evaluation tool. OBJECTIVE: To evaluate the measures of diagnostic accuracy of the OARs in the acute setting. METHODS: The OARs were applied to all appropriate ankle injuries at 2 colleges (athletics and club sports) and 21 high schools. The outcomes of OARs, diagnosis, and decision for referral were collected by the athletic trainers (ATs) at each of the locations. Contingency tables were created for evaluations completed within 1 h for which radiographs were obtained. From these data the sensitivity, specificity, positive and negative likelihood ratios, and positive and negative predictive values were calculated. RESULTS: The OARs met the criteria for radiographs in 100 of the 124 cases, of which 38 were actually referred for imaging. Based on radiographic findings in an acute setting, the OARs (n = 38) had a high sensitivity (.88) and are good predictors to rule out the presence of a fracture. Low specificity (0.00) results led to a high number of false positives and low positive predictive values (.18). CONCLUSION: When applied during the first hour after injury the OARs significantly overestimate the need for radiographs. However, a negative finding rules out the need to obtain radiographs. It appears the AT's decision making based on the totality of the examination findings is the best filter in determining referral for radiographs.

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)0.001
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 score0.022
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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