Quantitative magnetic resonance imaging evaluation of knee osteoarthritis progression over two years and correlation with clinical symptoms and radiologic changes
Bibliographic record
Abstract
OBJECTIVE: To evaluate the change in osteoarthritic (OA) knee cartilage volume over a two-year period with the use of magnetic resonance imaging (MRI) and to correlate the MRI changes with radiologic changes. METHODS: Thirty-two patients with symptomatic knee OA underwent MRI of the knee at baseline and at 6, 12, 18, and 24 months. Loss of cartilage volumes were computed and contrasted with changes in clinical variables for OA and with standardized semiflexed knee radiographs at baseline at 1 and 2 years. RESULTS: Progression of cartilage loss at all followup points was statistically significant (P < 0.0001), with a mean +/- SD of 3.8 +/- 5.1% for global cartilage loss and 4.3 +/- 6.5% for medial compartment cartilage loss at 6 months, 3.6 +/- 5.1% and 4.2 +/- 7.5% at 12 months, and 6.1 +/- 7.2% and 7.6 +/- 8.6% at 24 months. Discriminant function analysis identified 2 groups of patients, those who progressed slowly (<2% of global cartilage loss; n = 21) and those who progressed rapidly (>15% of global cartilage loss; n = 11) over the 2 years of study. At baseline, there was a greater proportion of women (P = 0.001), a lower range of motion (P = 0.01), a greater circumference and higher level of pain (P = 0.05) and stiffness in the study knee, and a higher body mass index in the fast progressor group compared with the slow progressor group. No statistical correlation between loss of cartilage volume and radiographic changes was seen. CONCLUSION: Quantitative MRI can measure the progression of knee OA precisely and can help to identify patients with rapidly progressing disease. These findings indicate that MRI could be helpful in assessing the effects of treatment with structure-modifying agents in 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) | 0.000 | 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".