The efficacy of the leg swing and quadriceps strengthening exercises versus platelet-rich plasma and hyaluronic acid combination therapy for knee osteoarthritis: A retrospective comparative study
Bibliographic record
Abstract
The aim of this was to investigate the efficacy of physical exercise (leg swing and quadriceps strengthening exercises) versus platelet-rich plasma (PRP) and hyaluronic acid (HA) combination therapy. From January 2020 to August 2021, 106 patients with Kellgren-Lawrence Grade I-III knee osteoarthritis were divided into leg swing and quadriceps strengthening exercises (Group A) and intra-articular combination injections of PRP and HA (Group B) according to the treatment strategies. Patients in Group A received regular leg swing and quadriceps strengthening exercises for 3 months. Patients in Group B received 2 intra-articular combination injections of PRP (2 mL) and HA (2 mL) every 2 weeks. The primary outcome measures were the Visual Analogue Scale (VAS) and the Western Ontario and McMaster Universities (WOMAC) score. Secondary outcomes included single leg stance test and functional activity by 2-minute walk test and time up and go test. All outcomes were evaluated at baseline and again 1, 3, 6, and 12 months. The VAS and WOMAC scores were similar in both groups at 1 and 3 months after treatment (P > .05); however, Group A patients had significantly superior VAS and WOMAC scores than Group B patients at 6 and 12 months after treatment. For the single leg stance test, 2-minute walk test, and time up and go test, Group A patients were significantly superior to Group B throughout follow-up (P < .001). The leg swing and quadriceps strengthening exercises resulted in a significantly better clinical outcomes than the combined PRP and HA therapy, with a sustained lower pain score and improved quality of life, balance ability, and functional activity within 12 months.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".