An Indigenous Dynamic Multiaxial Adjustable Shoulder Splint for the Management of Shoulder Subluxation
Bibliographic record
Abstract
Background: The main problem with shoulder subluxation is the instability of the shoulder joint. The anatomy of this joint permits a large range of movement, but it sacrifices stability. Available splint options for shoulder subluxations are a lot but they are not providing the full range of motion of the joint. Considering this we have designed and developed a new Dynamic Multiaxial Adjustable Shoulder Splint. Objective: This study aimed to design an Indigenous Dynamic Multiaxial Adjustable Shoulder Splint for the Management of shoulder subluxation which will reduce the subluxation and pain. Study design: A case report Methods: A 52-years-old lady diagnosed with right shoulder subluxation was fitted with the newly designed Indigenous Dynamic Multiaxial Adjustable Shoulder Splint for the reduction of pain and subluxation. The Western Ontario Shoulder Instability Index (WOSI) was assessed to measure the shoulder-related quality of life in patients with symptomatic shoulder instability. Before and after the test was conducted with and without the newly designed splint with an intervention period of 4 months. Results: The WOSI score of 9.8% was achieved after the intervention period of 4 months and the reduction of subluxation was immediate and provided total relief from the pain. Conclusion: This Indigenous Dynamic Multiaxial Adjustable Shoulder Splint can be considered as a very excellent splint for the orthotic management of shoulder subluxation and it also can be used as a standard design that can be prescribed for patients with brachial plexus injury, frozen shoulder and rotator cuff injury, post-operative cases, etc. Key words: Shoulder Subluxation, Multiaxial, shoulder splint, WOSI score.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".