Intra-articular injection of gold micro-particles with hyaluronic acid for painful knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Recently, in an open pilot study, we found up to two years, a potential pain-relieving effect of intra-articular gold micro-particles using the patient's synovial fluid for patients with knee osteoarthritis (KOA). During the study the excluded group of patients, due to multisite pain, co-morbidities, and other exclusion criteria., received intra-articular gold micro-particles using hyaluronic acid,. We aimed to identify if pre-treatment characteristics influence the global outcome two years after intra-articular treatment for painful KOA with gold microparticles using hyaluronic acid. METHODS: Using hyaluronic acid as the carrier, 136 patients with KOA received intraarticular injections with 20 mg gold microparticles (72.000 particles, 20-40 μm in diameter). In the analysis, we included the Global Rating of Change Scale, Pain Detect Questionnaire (PDQ), Body Mass Index (BMI), and Kellgren & Lawrence score at the inclusion, Western Ontario, and McMaster Universities Osteoarthritis Index (WOMAC) sub-scores for pain, stiffness, and function at inclusion and two years. RESULTS: On the Global Rating Change Scale, 69.1% of patients reported a positive effect, 28.7% no effect, and 2.2% worse. PDQ and the three WOMAC subscores all improved at two years of follow-up. PDQ ≥ 13 (P = 0.028), BMI (P = 0.022) and Kellgren & Lawrence grade 4 (P = 0.028) at inclusion reduced the effect with a minor odds ratio compared to the baseline effect of treatment (P = 0.025). WOMAC subscores at inclusion did not influence the outcome (P > 0.5). CONCLUSIONS: Severe osteoarthritis, obesity, and neuropathic pain, reduced the effect of intra-articular gold microparticles for knee OA. TRIAL REGISTRATION: The study followed the principles of the Declaration of Helsinki and was approved by the local ethics committee of the North Denmark Region by 27/07/2016 (N-20,160,045). The regional data protection agency approved the project by 06/07/2016 (2008-58-0028, ID 2016 - 116) and registered in ClinicalTrial.Gov by 04/01/2018 (NCT03389906).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".