Examining outcome of early physician specialist assessment in injured workers with shoulder complaints
Bibliographic record
Abstract
BACKGROUND: There is minimal research on demographics, type of injury and diagnosis of injured workers with shoulder problems. The purposes of this study were: 1) to document the demographics of patients with shoulder complaints referred to an Early Shoulder Physician Assessment (ESPA) Program and to describe the recommended management, and 2) to examine the relationship between patient characteristics and their subjective complaints of pain and functional difficulty. METHODS: This study involved a retrospective review of electronic files of injured workers mostly seen within the first 16 weeks of injury or recurrence. Measures of functional difficulty and pain were the Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH) and Numeric Pain Scale (NPS). RESULTS: Files of 550 consecutive patients, 260 females (47%), 290 men (53%) were examined. The average age was 49 (SD = 11, range 22-77), with 28 (5%) patients being 65 years of age or older. Patients who were not working were the most disabled group based on Quick DASH (F = 49.93, p < 0.0001) and NPS (F = 10.24, p = 0.002). Patients who were working full time performing regular duties were the least disabled according to both measures, the QuickDASH (F = 10.24, p = 0.002) and NPS (F = 7.57, p = 0.006). Patients waiting more than 16 weeks were slightly older (53 years of age vs. 49, p = 0.045) than those who met the criteria for early assessment with similar levels of pain and functional difficulty. Biceps pathology had the highest prevalence (37%). Full thickness tear had a prevalence of 14%. Instability, labral lesions and osteoarthritis of glenohumeral joint were uncommon conditions (3, 2 and 1% respectively). Fifty-five patients (10%) were surgical candidates and had higher scores on QuickDASH (F = 7.16, p = 0.008) and NPS (F = 4.24, p = 0.04) compared to those who did not require surgery. CONCLUSIONS: This study provides information on characteristics and prevalence of important variables in injured workers with shoulder problems and highlights the impact of these characteristics on pain and disability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".