Relationship Between Clinical and Radiographic Findings in Osteoarthritis Knee: A Cross-Sectional Study
Bibliographic record
Abstract
Several studies have suggested that there is a high discrepancy between clinical and radiographic knee osteoarthritis. The objectives of this study were to examine association between radiographic classification and clinical manifestations of knee osteoarthritis, and to determine if the assessment of individual radiographic features was superior to the general radiographic scale in establishing such a relationship. A total of 125 patients with knee osteoarthritis were enrolled in this study. Radiographic features were assessed with the Kellgren-Lawrence grade scale for general radiographic grading, and a line-drawing atlas for detailed radiographic analysis. The severity of knee pain, stiff ness, and disability were measured using the Western Ontario and McMaster Universities Osteoarthritis Index. Patients' age and pain duration were found to correlate significantly with knee pain, stiff ness, and disability. No association between general radiographic grading scale and clinical manifestations was found. However in detailed radiographic analysis, osteophyte site at the patellofemoral joint was found to correlate with knee stiff ness. In conclusion, radiographic scores were not found to be closely associated with the clinical features of knee osteoarthritis. The results of knee X-rays should not be used in isolation when a management decision is to be taken for patients with knee osteoarthritis.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".