Intervención de la terapia ocupacional en rizartrosis: revisión bibliográfica
Bibliographic record
Abstract
Objective: This review aims to identify the effects of different occupational therapy interventions in patients suffering from osteoarthritis of first carpometacarpal joint, to know the types of treatments available for occupational therapists, and to establish various tests and standardized scales that can be applied in the assessment of this condition. Methods: A literature review was carried out using five databases. Articles related to our study, which had been published in the last ten years (June 2007- June 2017) in English or Spanish, were examined. An additional criterion was selecting samples with patients aged between 18 and 65. Results: A total of eight articles were assessed in which occupational therapy has proved to have beneficial effects on maintaining the dynamic stability of the trapeziometacarpal joint, using different techniques such as joint protection, orthotic treatment, treatment of fine motor skills and manual exercises with the aim to improve joint range and muscle strength. Conclusion: There are some discrepancies about which method of treatment is the most appropriate as well as a consensus regarding the application of these therapies. In addition, the assessment tools for this pathology have been tested, these being the Visual Analog Scale (VAS), the Disabilities of the Arm, Shoulder and Hand (DASH), the Australian Canadian Osteoarthritis Hand Index (AUSCAN), the Purdue Pegboard and the O’Connor test.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".