Patients with non-operated traumatic primary or recurrent anterior shoulder dislocation have equally poor self-reported and measured shoulder function: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Patients with non-operated traumatic primary anterior shoulder dislocation (PASD) are assumed to have less shoulder impairment than patients with recurrent anterior shoulder dislocations (RASD). This may impact treatment decision strategy. The aim was to study whether patients with non-operated traumatic PASD have less shoulder impairment than those with RASD. METHODS: In a cross-sectional study baseline data from patients with PASD and RASD in a randomised controlled trial of non-operative shoulder exercise treatment were used. Shoulder function was self-reported (Western Ontario Shoulder Instability (WOSI), Tampa Scale of Kinesiophobia (TSK), General Health (EQ-5D-VAS), Numeric Pain Rating Scale (NPRS)), and measured (Constant-Murley shoulder Score (CMS total), CMS - Range of Motion (CMS-ROM, CMS - strength, proprioception, clinical tests). RESULTS: In total, 56 patients (34 (28 men) with PASD and 22 (21 men) with RASD) (mean age 26 years) participated. WOSI total was 1064 and 1048, and TSK above 37 (indicating high re-injury fear) was present in 33 (97%) and 21 (96%) of the groups with PASD and RASD, with no group difference. CMS total (66.4 and 70.4), CMS-ROM (28.7 and 31.5), CMS-strength (injured shoulder: 7.6 kg and 9.1 kg), proprioception and clinical tests were the same. Furthermore, 26 (76%) with PASD and 13 (59%) with RASD reported not to have received non-operative shoulder treatment. CONCLUSIONS: Non-operated patients with PASD and self-reported shoulder trouble three-six weeks after initial injury do not have less shoulder impairment (self-reportedly or objectively measured) than non-operated patients RASD and self-reported shoulder trouble three-six weeks after their latest shoulder dislocation event.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".