Comparison of diagnostic decision rules and structured data collection in assessment of acute ankle injury.
Bibliographic record
Abstract
BACKGROUND: Ankle decision rules help to determine which patients with ankle injuries should undergo radiography. However, these rules are limited by imperfect generalizability and sensitivity. The judgement of physicians, aided by structured data collection, is a potential alternative. We compared the diagnostic performance of 2 decision rules with the performance of physicians, aided by structured data collection, in ruling out fracture in patients with acute ankle injury. METHODS: Consecutive patients with acute ankle injury who visited the emergency department of a teaching community hospital in Amsterdam were included in the study. After taking the patient's history and performing a physical examination, the surgical resident in each case completed a specially developed structured data form incorporating all of the variables in the Ottawa and Leiden ankle rules, as well as some additional variables. The form then asked whether the resident thought radiography was necessary. Each patient then underwent ankle and midfoot radiography. The films were independently interpreted by a radiologist and a trauma surgeon, who were both blinded to the information on the data form. Sensitivity, specificity and the percentage of patients for whom radiography was recommended were the main outcome measures. RESULTS: Of 690 consecutive patients, 647 met the inclusion criteria. Fractures were observed in 74 (11%) of these patients. Sensitivity was 89% (95% confidence interval [CI] 80% to 95%) for the Ottawa ankle rules, 80% (95% CI 69% to 88%) for the Leiden ankle rule and 82% (95% CI 72% to 90%) for physicians' judgement. Specificity was 26% (95% CI 23% to 30%), 59% (95% CI 55% to 63%) and 68% (95% CI 64% to 71%) respectively. Radiography was recommended in 76% (95% CI 72% to 79%), 46% (95% CI 42% to 50%) and 38% (95% CI 34% to 42%) of cases respectively. The Ottawa rules missed 8 fractures, of which 1 was clinically significant, the Leiden rule missed 15 fractures, of which 5 were clinically significant, and the residents missed 13 fractures, of which 1 was clinically significant. INTERPRETATION: Physicians' judgement, aided by structured data collection, was similar to existing international and local decision rules in terms of sensitivity in identifying cases requiring radiography and may outperform these prediction rules in terms of minimizing radiographic examinations for patients with ankle trauma.
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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 | 0.001 |
| 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 | 0.000 |
| 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".