Functional outcome in knee osteoarthritis after dextrose prolotherapy intervention: A severity-based pilot study
Bibliographic record
Abstract
Background: Osteoarthritis currently remains a significant health problem due to its high prevalence and morbidity rate. Radiological examination is still used as a gold standard to determine the severity of knee osteoarthritis by using Kellgren-Lawrence grading. Dextrose prolotherapy has been known to be effective in treating pain in knee osteoarthritis, but none has compared the efficacy between mild and moderate-severe knee osteoarthritis. Objective: This study aims to compare the effectiveness of prolotherapy based on its radiological and symptomatic severity in knee osteoarthritis.Methods: In this pre-post study, the participants who underwent dextrose prolotherapy injection (25% intra-articular and 15% periarticular) for three sessions with four weeks intervals were grouped into mild (grade 1-2) and severe (grade 3-4) groups. Participants’ functional status was measured with Western Ontario and McMaster Universities’ arthritis index scores at baseline and week 12.Results: A total of 21 patients (average age 61.42 ± 8.33, BMI 26.81± 3.72) received three therapy sessions. Both groups had significantly better Western Ontario and McMaster Universities arthritis index scores than baseline (-22.57± 11.9; p = 0.002 and -15.42 ± 15.75; p = 0.003). All parameters were improved significantly (p <0.05) in both groups, except the stiffness score (p = 0.292; p = 0.057). There were no differences in functional outcome improvements in both groups (p > 0.05; CI 95%: -21.3 – 7.05).Conclusion: Prolotherapy effectively improves functional outcomes in all stages of knee osteoarthritis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".