28 A cochrane review of strategies to increase adoption of the ottawa ankle rules and reduce unnecessary imaging
Bibliographic record
Abstract
<h3>Objectives</h3> The aim of this review is to establish the effectiveness of existing strategies to increase adoption of the Ottawa Ankle Rules (OARs) and reduce ankle/foot imaging. <h3>Method</h3> We will conduct a Cochrane systematic review according to the Methodological Expectations of Cochrane Intervention Reviews standards, within the Cochrane Musculoskeletal Group. A comprehensive keyword search (combining terms synonymous with ‘implementation’ and ‘Ottawa Ankle Rules’) will be performed in MEDLINE, EMBASE, CINAHL, Cochrane CENTRAL, Scopus and Web of Science from the earliest record to the time of search. Additional articles will be identified by hand-searching references lists and forward searching of included articles. We will include randomised controlled trials, uncontrolled trials, and interrupted time-series investigating strategies to increase adoption of the OARs. The primary outcome will be documented adherence to the OARs. The proportion of unnecessary ankle/foot imaging requests and the total number of ankle/foot imaging requests will be secondary outcomes. Two reviewers will independently perform the selection of studies, extract key data (e.g. trial characteristics, intervention parameters, outcomes), and assess the risk of bias of included studies. <h3>Results</h3> We anticipate to have extracted all study data by the conference and are confident we will be able to present preliminary results. <h3>Conclusions</h3> Nearly 10% of people suffer an ankle injury in their life; but although less than 20% have a fracture, 70%–95% receive imaging. In the absence of a fracture, imaging does not inform management and exposes patients to unnecessary/potentially harmful radiation. The OARs are a clinical decision tool with nearly 100% sensitivity for ruling out ankle/foot fractures, thereby indicating those who don’t require imaging. These rules have been validated in numerous countries, endorsed in practice guidelines for over two decades, and more recently included in Choosing Wisely lists. Successful implementation of the OARs could reduce unnecessary ankle/foot imaging and time spent in emergency departments. However, the OARs aren’t commonly used in practice. Identifying effective strategies to increase adoption of the OARs could reduce unnecessary ankle/foot imaging among various healthcare professionals and guide implementation activities to reduce low-value care across health disciplines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".