Identification of early response to hypertonic dextrose prolotherapy markers in knee osteoarthritis patients by an inflammation-related cytokine array
Bibliographic record
Abstract
Abstract BACKGROUND/AIMOsteoarthritis (OA) is one of the most common forms of arthritis, and hypertonic dextrose prolotherapy has long been used clinically to treat knee OA. The aim of this study was to investigate the inflammation-related protein-expression profile characterizing the efficacy of the hypertonic dextrose prolotherapy in knee OA as prognostic markers.METHODSOA patients over the age of 65 were recruited for Western Ontario McMaster University Osteoarthritis (WOMAC) index, knee X ray evaluation and knee joint synovial fluid analysis before and after hypertonic dextrose prolotherapy. The expressions of inflammation-related factors were measured using a novel cytokine antibody array methodology. The cytokine levels were quantified by quantitative protein expression and analyzed by ELISA using the patients’ knee-joint synovial fluid. The WOMAC Index and minimum joint space width prior to receiving the intra-articular injection and at 2-week intervals were compared.RESULTS12 patients who received OA intervention were enrolled and finally a clinical evaluation of 12 knee joints and knee synovial fluid samples were analyzed. In this study, after receiving hypertonic dextrose prolotherapy, the OA patients clearly demonstrated a significant improvement in WOMAC index and increasing tendency in the medial minimum joint space width after intervention. Meanwhile, we observed a significantly associated tendency between the high-glucose treatment of knee OA and the upregulation of MMP2, TIMP-1, EGF, CXCL9 and IL-22. These findings provide knee OA patients receiving hypertonic dextrose prolotherapy, which accompanying with the improvement of knee pain, stiffness, and function and increasing tendency in the medial minimum joint space width.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".