Correlation between clinical, radiological and arthroscopic findings in cases of osteoarthritis of knee joint
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is the most common degenerative joint disorder and a major public health problem throughout the world. The knees are the most commonly affected joints. In view of multiple conflicting reports in the literature the present study was undertaken to study the correlation amongst radiological, arthroscopic and pain findings in knee OA patients to facilitate early and precise diagnosis leading to appropriate and timely treatment. Methods: Total 53 (39 female and 14 male) cases of primary OA were screened and selected for our study. Apley’s pain score equated to Visual Analogue Score and Western Ontario and MacMaster Universities Osteoarthritis score (WOMAC) sub scales were used for assessment of pain, stiffness and physical function respectively. Radiographic evaluation were done according to Kellgren-Lawrence Grading scale (X-ray) and modification of Outerbridge classification system (MRI). Outerbridge classification system was used to assess arthroscopic findings. Results: Clinical symptom of pain had statistically significant correlation with stiffness, physical disability, radiological severity and arthroscopic findings. Stiffness and physical disability scores individually doesn’t have any statistically significant correlation with MRI and arthroscopic severity. Radiological findings were found to corroborate with the arthroscopic findings significantly. Conclusions: Radiological and clinical findings in combination should be considered in concluding the final diagnosis and treatment of OA knee. Improvised criteria for precise diagnosis yet to be evolved.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".