Computer Use Associated With Poor Long-Term Prognosis of Conservatively Managed Lateral Epicondylalgia
Bibliographic record
Abstract
STUDY DESIGN: Multicenter prospective design with a cohort of patients with lateral epicondylalgia commencing physical therapy. OBJECTIVE: To identify key factors associated with long-term prognosis of conservatively managed lateral epicondylalgia. BACKGROUND: The response to conservative management of lateral epicondylalgia is inconsistent and the rate of recovery varies widely among individuals. The reasons for these discrepancies are not understood. The identification of factors associated with prognosis will aid in the prediction of patient outcomes. METHODS AND MEASURES: Sixty patients with lateral epicondylalgia, recruited from 9 sports medicine clinics and 2 hospital outpatient physical therapy departments in Ontario, Canada, were followed for 6 months. A baseline clinical assessment was conducted on each participant using standard physical therapy techniques. The Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire and a 100-mm pain visual analog scale (VAS) were completed at baseline and 6 months later. RESULTS: The key factor associated with both 6-month DASH and pain VAS scores was repetitive-work tasks (DASH, 9.8 [P < .011; pain VAS, 13.1 mm [P = .0105]). A subanalysis indicated that women were more likely than men to have cervical joint signs and, among women, positive cervical articular signs were also associated with higher final DASH and pain VAS scores. CONCLUSIONS: Although many of the participants identified sports activities as the cause of their injury, these findings emphasize the importance that a patient's work tasks can have on recovery of lateral epicondylalgia. This would suggest that management should perhaps focus on work stations, postures, and behaviors.
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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 | 0.000 | 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 | 0.000 |
| 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".