Associations between shoulder symptoms and concomitant pathology in patients with traumatic supraspinatus tears
Bibliographic record
Abstract
BACKGROUND: The association between concomitant pathologic characteristics and preoperative symptoms in patients identified as eligible for surgical rotator cuff repair has been sparsely evaluated. The purpose was to explore the associations between preoperative shoulder symptoms and additional structural pathology or injuries identified during surgery in patients with traumatic supraspinatus tears. METHODS: This was a cross-sectional study including patients with traumatic supraspinatus tears. Preoperatively, patients reported pain and disability using a numeric pain rating scale from 0 to 10 and the Western Ontario Rotator Cuff Index. During surgery, the presence of prespecified structural injuries and pathologies including a full-thickness or partial supraspinatus tear, infraspinatus tear, subscapularis tear, hooked acromion, acromioclavicular joint osteoarthritis, biceps tendon pathology, labral tear, and cartilage lesion was recorded. Linear regression and analysis of covariance were used to assess associations. RESULTS: A total of 87 patients (52 male patients, 60%) were included (mean age, 60 years; standard deviation, 9.2 years). Of these patients, 69 (79%) had a full-thickness supraspinatus tear and 18 (21%) had a partial-thickness tear. Concomitant structural pathology was found in 79 patients (91%). No association was found between the number of structural shoulder pathologies and preoperative numeric pain rating scale or Western Ontario Rotator Cuff Index score, and no particular concomitant pathology was associated with worse patient-reported symptoms. CONCLUSION: Pathology of the infraspinatus and subscapularis and other structural joint pathologies concomitant with supraspinatus tears were not correlated with preoperative self-reported pain and disability in patients scheduled to undergo rotator cuff surgery, suggesting that concomitant pathology adds little to the symptoms in patients with a traumatic supraspinatus tear.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".