Association between radiographic joint space narrowing, function, pain and muscle power in severe osteoarthritis of the knee
Bibliographic record
Abstract
OBJECTIVE: To examine the association between radiographic classification of severe knee osteoarthritis and measurements of function, pain and power. DESIGN: Cross-sectional study. SETTING: Specialist orthopaedic hospital. SUBJECTS: One hundred and twenty-three patients on the waiting list for elective knee arthroplasty. OUTCOME MEASURES: Weight-bearing antero-posterior radiographs scored for severity of osteoarthritis using the Kellgren and Lawrence scale. Function measured using the function subscale of the WOMAC (Western Ontario and McMaster Universities) index, timed tests of walking speed and sit-to-stand. Pain measured using the pain subscale of the WOMAC index and a visual analogue scale. Extensor strength of the lower limb measured with the leg extensor power rig. RESULTS: Within any radiographic grade there was considerable variation in function: WOMAC function for patients with grade 2 mean 64 (47-86), grade 3 mean 47 (12-89) grade 4 mean 45 (2-92). There was poor correlation between radiographic score function, pain or muscle power, with no statistically significant associations. A wide range of scores was also seen within patients with the same radiographic grade. CONCLUSIONS: Radiographic score was not found to be closely associated with function. Amongst patients with the same radiographic score there was considerable variation in function, pain and power.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".