Clinical Outcomes of Hypertonic Dextrose Prolotherapy Injection in Obese Patients with Knee Osteoarthritis: A Quasi-Experimental Study
Bibliographic record
Abstract
Background: Obesity is a major risk factor for knee osteoarthritis (KOA), contributing to pain, reduced joint function, and decreased quality of life. Hypertonic dextrose prolotherapy (HDP) has emerged as a potential treatment to lessen pain and improve function in KOA. This study aimed to observe the clinical outcomes of HDP injections in obese patients with KOA.Methods: A quasi-experimental study was conducted in 2023, involved obese patients diagnosed with KOA. Participants were divided into two groups: an intervention group receiving HDP injections and a control group receiving normal saline (NS) injections. Clinical outcomes were assessed using the Numeric Rating Scale (NRS) for pain and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) before intervention, and at two and six weeks after intervention. Intergroup and intragroup mean differences were analyzed, with a significance value of p<0.05.Results: A total of 38 participants were included, with 20 assigned to the HDP group and 18 to the control group. Intragroup analysis showed a significant reduction in NRS scores in both groups (p<0.001), whereas no significant intragroup change was observed in WOMAC scores. Intergroup analysis showed significantly greater improvement in both NRS and WOMAC scores in the HDP group compared with the control group at two and six weeks after intervention (p<0.001).Conclusions: HDP injections improve clinical outcomes in obese patients with KOA, particularly in reducing pain intensity and improving functional status. Pain reduction may support participation in exercise and weight management programs, although persistent obesity may increase the risk of KOA recurrence.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".