The tuning fork test--a useful tool for improving specificity in "Ottawa positive" patients after ankle inversion injury
Bibliographic record
Abstract
The Ottawa ankle rules are a clinical instrument calibrated towards a high sensitivity in order not to miss any fractures of the ankle or mid-foot. This is at the cost of a mean specificity of around only 32%. The aim of this study was to determine the suitability of tuning fork testing in combination with existing Ottawa guidance for increasing the specificity in detecting fractures of the lateral malleolus. A prospective pilot study was carried out, in which a single trained investigator examined all patients with already "Ottawa positive" findings for possible lateral malleolus injury by applying a tuning fork (C(o) 128 Hz). The tuning fork test findings were compared with formal reports of plain ankle radiographs using simple cross-table analysis. The observed prevalence of ankle fractures was 5 of 49 (10%). Sensitivity and specificity were calculated as 100% and 61%, respectively, for tuning fork testing on the tip of the lateral malleolus (TLM), and as 100% and 95%, respectively, for testing on the distal fibula shaft (DFS). The associated positive and negative likelihood ratios were 2.59 and 0 (TLM), and 22 and 0 (DFS), respectively. The data were significant, with p = 0.014 (TLM) and p<0.001 (DFS). This study suggests that additional tuning fork testing of "Ottawa positive" patients may lead to a marked reduction in ankle radiographs, with consequently reduced radiation exposure and journey time. This may be particularly relevant in situations where radiological facilities are not readily available (expedition medicine) or where access to these has to be prioritised (major incidents, natural catastrophes).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".