Correlation Between Changes in Global Knee Structures Assessed by Magnetic Resonance Imaging and Radiographic Osteoarthritis Changes Over Ten Years in a Midlife Cohort
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to describe the correlation between changes in structural abnormalities assessed on magnetic resonance imaging (MRI) and change in radiographic osteoarthritis (OA) over 10 years in a midlife cohort. METHODS: A total of 211 participants (mean age 45 years [range 26-61 years], 57% female) were studied at baseline, 2 years, and 10 years. Approximately one-half were adult offspring of subjects who had undergone knee replacement for OA and the remainders were randomly selected controls. Joint space narrowing (JSN) and osteophytes were assessed from radiographs, while cartilage volume, cartilage defects, and meniscal tears/extrusion were assessed from MRI. Spearman ranked correlation analysis was used to describe the correlation between structural changes assessed on MRI and radiographs. Only medial tibiofemoral compartment results are presented, as the lateral compartment had limited change. RESULTS: Over 10 years, change in meniscal tears showed a moderate independent correlation with change in both JSN (ρ = +0.37, P < 0.01) and osteophytes (ρ = +0.31, P < 0.01) in the adjusted analysis. Meniscal extrusion (ρ = +0.22, P < 0.01) and cartilage defects (ρ = +0.16, P < 0.04) showed a slightly weaker independent correlation with JSN in the adjusted analysis, whereas cartilage volume loss showed no significant correlation with either of the 2 radiographic outcomes. CONCLUSION: Change in JSN is correlated with change in meniscal tears and, to a lesser extent, with meniscal extrusion and cartilage defects. In this sample, change in JSN is a composite measure that does not reflect cartilage volume loss, prompting the review of the use of JSN as an outcome measure in chondro-protective drug trials.
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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 | 0.001 | 0.002 |
| 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".