Arthroscopic Bankart Repair after Anterior Traumatic Shoulder Dislocation in Workers
Bibliographic record
Abstract
Objectives: The objective of this study was to evaluate clinical results in workers after Arthroscopic Bankart repair for traumatic unidirectional shoulder dislocation. Methods: A total of 45 patients (42 male- 3 female) meet the inclusion criteria: traumatic anterior dislocation, workers´ compensation patient, minimum of 2 years follow-up and exclusion criteria: bony Bankart >25%, engaging Hill Sachs, previous surgery, rotator cuff injury. Number of dislocations were 1 in 35 patients, 2 in 7 patients and 3 in 3 patients. Artroscopic Bankart repair was performed by a single surgeon. UCLA shoulder Score and ROWE score for shoulder instability were scored for clinical assessment. The mean follow up was 64 (SD+- 21.6) month with a mean age of 30 (SD+-10) years. Type of work and workload was recorded according to Canadian classification and dictionary of occupations. Time to return to work was also recorded. Statistical analysis was performed at the center for biostatistics at Facultad de Ciencias Medicas, Universidad Nacional del Litoral using SPSS 23.0-IBM. Results: The mean UCLA Shoulder Score was 33 (SD+-2) and ROWE Score 95 (SD +-7), none of the patients presented recurrent dislocation at the time of follow up. Time to return to work was mean 123 days (+-60 SD) of whom 52% were heavy workers, 39% medium and 9% light workers. All patients except one could return to his previous level of work. Pearsons bi variate correlation coefficient between days to return to work between heavy and medium/light workers was not significative (p>0,05) but in heavy workers return to work take more days than in medium/light workers. Age and return to work with 35 years as a cut point was not significative either. Conclusion: Workers treated with Arthroscopic Bankart repair after traumatic unilateral dislocation, presents good results and high rate of return to work at the previous level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".