Improving the Rapid and Reliable Diagnosis of Complete Distal Biceps Tendon Rupture
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Bibliographic record
Abstract
BACKGROUND: Diagnosis of complete distal biceps tendon rupture (DBTR) is frequently missed or delayed on clinical examination. No single clinical test, including MRI, has demonstrated 100% efficacy in assessing the integrity of the distal biceps tendon. HYPOTHESIS: Combining 3 validated clinical tests for identifying complete rupture can maximize a true-positive diagnosis for complete DBTR without the need for confirmatory soft tissue imaging when performed in concert with other important factors from the history and clinical examination. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: The hook test, the passive forearm pronation (PFP) test, and the biceps crease interval (BCI) test were applied in sequence in conjunction with a standard patient history and physical examination on 48 patients with suspected distal biceps tendon injuries. If results on all 3 special tests were positive for complete rupture, the patient was referred for surgical repair; diagnosis was confirmed intraoperatively. If results on all 3 special tests were negative, diagnosis was confirmed with soft tissue imaging and patients were managed nonoperatively. If results of the 3 tests were not in agreement, soft tissue imaging was used to clarify the disagreement and to confirm the diagnosis. RESULTS: Thirty-five patients had unequivocal results based on history, physical examination, and special tests. Thirty-two tested in agreement positive for complete rupture, which were confirmed intraoperatively. Three tested in agreement negative, with subsequent imaging confirming partial rupture. Thirteen patients had equivocal special test results; soft tissue imaging suggested complete rupture in 10 and partial rupture in 3. CONCLUSION: Application in sequence of the hook test, the PFP test, and the BCI test results in 100% sensitivity and specificity when the outcomes on all 3 special tests are in agreement.
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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 | 0.001 | 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 | 0.001 |
| 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 it