Comparing the Effects of Corticosteroid Injections and Resistance Exercise on Knee Osteoarthritis Patients: A Systematic Review.
Bibliographic record
Abstract
PURPOSE: To evaluate research on the effectiveness of intra-articular corticosteroids injections compared with resistance exercise on pain, stiffness, and function among patients diagnosed with knee osteoarthritis. METHODS: Using the PRISMA guidelines, the authors performed a systematic review of randomized controlled trials (RCTs) in PubMed and EBSCOhost published between January 2012 and October 2022. The authors used keywords to identify studies. After screening the abstracts, reviewers used two screening tools to evaluate for validity and strength of each RCT. Full text of selected articles was critically appraised and narrative analysis was performed. The outcome used to determine effectiveness of the interventions was the Western Ontario McMaster University Osteoarthritis Index (WOMAC). RESULTS: Of the 69,056 articles identified during the preliminary search, 8 met the inclusion criteria for use in the study. Three studies involved resistance exercise, and 5 studies involved corticosteroids. Of the 3 resistance studies, 2 had significant changes in WOMAC scores. Of the 5 studies on corticosteroid injections, 4 had significant changes in WOMAC scores. CONCLUSION: Evidence from this review suggests that there is a significant improvement in WOMAC scores for both intervention groups. Although an analysis of research evidence suggests that there is no superior treatment for knee osteoarthritis between corticosteroid injections and resistance exercise, it is important to consider contextual and environmental factors before recommending either treatment.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".