Treatment of osteoarthritis of the knee with bracing: a scoping review
Bibliographic record
Abstract
Knee osteoarthritis is a leading cause of disability around the world. Knee bracing provides a conservative management option for symptom relief. A variety of different bracing types, manufacturers and products are currently available on the market. The goal of this study is to examine the current state of the literature regarding the treatment of knee osteoarthritis with unloader bracing, specifically examining the representation of specific brace types, manufacturers and models within the literature. A scoping review technique was used because of its ability to evaluate research activity within an area of study and identify gaps within the literature. A thorough search of the MEDLINE database was conducted for articles where a knee brace model was identified, and we identified characteristics of the studies to evaluate important information about the body of literature related to knee bracing for the treatment of osteoarthritis. Fifty eligible studies were identified. The majority of studies have been published in the United States, and a large increase in the number of publications in this field was seen between 2010-2014. The most prominent study type was prospective comparative studies (44%), however there is a lack of randomized controlled trials (6%) within the literature. The most prominent hinge type within the literature is the dual hinge push brace, followed by the single hinge pull. While a large increase in the number of studies evaluating the treatment of knee osteoarthritis with bracing has occurred in the past 5 years, there is a lack of high quality studies evaluating the efficacy of the technique, as well as a lack of studies comparing bracing types and models.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".