Association between statins and progression of osteoarthritis features on magnetic resonance imaging in a predominantly pre-radiographic cohort: the Vancouver Longitudinal Study of Early Knee Osteoarthritis (VALSEKO): a cohort study
Bibliographic record
Abstract
BACKGROUND: To evaluate the effect of statin use on osteoarthritis (OA) incidence/progression using magnetic resonance imaging (MRI) in a population-based cohort with predominantly pre-radiographic knee OA. METHODS: A cohort aged 40-79 years with knee pain was recruited using random population sampling and followed for 7 years. Baseline exclusions were inflammatory arthritis, recent knee surgery/injury, and inability to undergo MRI. At baseline, current statin use was ascertained. Baseline and follow-up MRIs were read semi-quantitatively for cartilage damage (grade 0-4, 0/1 collapsed, 6 regions), osteophytes (grade 0-3, 8 regions), bone marrow lesions (BML) (grade 0-3, 6 regions) and effusion (grade 0-3). The primary outcome was cartilage damage incidence/progression, while secondary outcomes were incidence/progression of osteophytes, BML, and effusion, each defined as an increase by ≥1 grade at any region. To ensure population representative samples, sample weights were used. Logistic regression was used to assess the association of statin use at baseline with incidence/progression of MRI outcomes. Analyses were adjusted for sex, age, BMI, and multiple comorbidities requiring statin therapy. RESULTS: Of 255 participants evaluated at baseline, 122 completed the 7-year follow-up. Statin use was not significantly associated with progression of cartilage damage (OR 0.82; 95% CI 0.17, 4.06), osteophytes (OR 3.48; 95% CI 0.40, 30.31), BML (OR 0.61; 95% CI 0.12, 3.02), or effusion (OR 2.38; 95% CI 0.42, 13.63), after adjusting for confounders. CONCLUSION: In this population-based cohort of predominantly pre-radiographic knee OA, statins did not affect MRI incidence/progression of cartilage damage, BML, osteophytes or effusion. Therefore, statin use does not appear to affect people with pre-radiographic stages of knee OA.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".