Can low-dose methotrexate reduce effusion-synovitis and symptoms in patients with mid- to late-stage knee osteoarthritis? Study protocol for a randomised, double-blind, and placebo-controlled trial
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is a common chronic disease in older adults. Currently, there are no effective therapies to reduce disease severity and progression of knee OA (KOA), particularly in mid- to late-stages. This study aims to examine the effect of methotrexate (MTX) on knee effusion-synovitis and pain in symptomatic patients with mid- to late-stage KOA. METHODS/DESIGN: This protocol describes a multicentre randomised placebo-controlled clinical trial aiming to recruit 200 participants with mid- to late-stage symptomatic KOA and with effusion-synovitis grade of ≥ 2. Participants will be randomly allocated to the MTX group (start from 5 mg per week for the first 2 weeks and increase to 10 mg per week for the second 2 weeks and 15 mg per week for the remaining period if tolerated) or the placebo group. Primary outcomes are effusion-synovitis size measured by magnetic resonance imaging (MRI) and knee pain assessed by visual analogue scale (VAS). Secondary outcomes are signal intensity alteration within infrapatellar fat pad (IPFP) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score and subscores, and the Outcome Measures in Rheumatology Arthritis Clinical Trials-Osteoarthritis Research Society International (OMERACT-OARSI) responders. Both intention-to-treat and per-protocol analyses will be performed. DISCUSSION: If MTX intervention can relieve symptoms and reduce inflammation in patients with mid- to late-stage KOA, it has the potential for significant clinical and public health impact as this low-cost and commonly used intervention would delay the time to knee replacement, leading to substantial cost savings and improve quality of life. TRIAL REGISTRATION: ClinicalTrials.gov NCT03815448 . Registered on 21 January 2019.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.014 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".