Diagnostic accuracy and potential triage utility of the Shetty test in foot and ankle trauma: a cross-sectional study
Bibliographic record
Abstract
Background/aim: Foot and ankle trauma represents a common reason for emergency department visits. While the majority of cases involve soft tissue injuries, radiographic imaging is frequently overutilized due to concerns about missed fractures, leading to increased costs and emergency department crowding. The Shetty test, a recently introduced clinical decision rule, may serve as a simpler alternative to established tools such as the Ottawa ankle rules. This study aimed to assess the diagnostic accuracy of the Shetty test and its potential role as a supportive tool within existing triage systems for patients presenting with foot and ankle trauma. Materials and methods: In this cross-sectional study, 229 adult patients with isolated foot or ankle trauma were evaluated in the emergency department. All participants underwent the Shetty test and standard radiographic imaging. The Shetty test was performed by trained emergency physicians prior to imaging; a positive result was defined as an inability to apply downward pressure due to pain. Diagnostic accuracy metrics-including sensitivity, specificity, positive predictive value, and negative predictive value-were calculated using radiographic findings as the reference standard. Results: Fractures were identified in 25.3% of cases. The Shetty test demonstrated a sensitivity of 77.6%, specificity of 60.8%, positive predictive value of 40.2%, and a high negative predictive value of 88.9%. Among patients with confirmed fractures, 77.6% had a positive test result. The test performed best in ruling out displaced and incomplete fractures, and results showed significant correlation with both physical findings and imaging outcomes. Conclusion: The Shetty test exhibited moderate sensitivity and specificity, alongside a high negative predictive value, supporting its use as a reliable rule-out tool for foot and ankle fractures. Its simplicity, ease of application, and diagnostic potential make it a promising triage adjunct to optimize emergency department resource use. Prospective multicenter validation is warranted before broad clinical adoption.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".