Quebec Decision Rule in Determining the Need for Radiography in Reduction of Shoulder Dislocation; a Diagnostic Accuracy Study.
Bibliographic record
Abstract
INTRODUCTION: The Quebec Decision Rule (QDR) has been developed for deciding on the necessity of radiography for patients with shoulder dislocation. This study aimed to investigate the diagnostic value of QDR in this regard. METHOD: This diagnostic accuracy study was conducted on patients with shoulder dislocation visiting the emergency department. After filling out the QDR-based checklist for all patients, they underwent radiography and the obtained radiography results were compared to QDR-based clinical diagnostic findings. RESULTS: 143 patients with the mean age of 32.1±12 years were evaluated (88.8% males). Sensitivity, specificity, and positive and negative predictive values of QDR were 50%, 58.2%, 3.3%, and 97.6%, respectively. The sensitivity and specificity were 100% and 50% in patients >40 years old, and 33.3% and 59.8% in those <40 years old. These indices were 33.3% and 60.4%, respectively, in the male sex and 100% and 40% in the female sex. CONCLUSION: Quebec decision rule holds promise to diagnose concomitant fractures in patients over the age of 40 with 100% sensitivity, thereby reducing the number of radiographies by 50% without causing diagnostic errors. In contrast, this criterion proved inefficient in patients younger than 40. .
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".