[Study on the relationship between severe knee osteoarthritis and bone marrow edema].
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between bone marrow edema and pathological changes, symptoms and signs of severe knee osteoarthritis. METHODS: . The degree of bone marrow edema was evaluated by knee whole oragan magnetic resonance imaging score (WORMS). The degree of knee osteoarthritis was evaluated by Kellgren- Lawrence(K-L) grade and Western Ontario and McMaster University Osteoarthritis Index (WOMAC). The degree of joint pain was evaluated by visual analogue scale(VAS) and WOMAC pain score, the joint signs were evaluated by tenderness, percussion pain, joint swelling and joint range of motion. To explore the relationship between bone marrow edema and knee osteoarthritis, the prevalence of bone marrow edema and K-L grade were compared between the two groups. Furthermore the WORMS score and WOMAC index, pain-related score, and sign-related score correlation coefficient were analyzed to further explore the relationship between bone marrow edema and knee osteoarthritis index, joint pain symptoms and signs. RESULTS: <0.001). CONCLUSION: Our study suggests that severe knee osteoarthritis is associated with an increased risk of bone marrow edema. Bone marrow edema can also lead to knee osteoarthritis joint pain, with percussion pain being a positive sign, but tenderness, joint swelling and limitation of activity are not significantly related to bone marrow edema.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 0.001 |
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".