Primary Osteoarthritis Knee: establishing its cause, pathogenesis and treatment -A Prospective Case-Control Study
Bibliographic record
Abstract
Background: The objectives of this analytical study were to compare two scores, Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), Euroqol Group Health Status Score through Visual Analog Scale (EQVAS); Deficient Full Flexion (DFF) and Deficient Full Extension of knee at the beginning and end-point in two, Trial (G1) and Control (G2) groups of Primary Osteoarthritis Knee patients. Material and Methods: In this study total patients were 125, in G1 - 100 and in G2 - 25. G1 group received hypothesized treatment, contracture correction therapy (CCT) while G2 did no therapy. WOMAC determination done by the questionnaire; EQVAS by vertical-scale and deficiencies by goniometer at 0, 6, 12 and 24 weeks. The CCT consisted of eight body postures, aimed to provide passive flexion or passive extension. Results: The CCT receiving was associated with recovery (P 0.00) while non-receiving with deterioration (P 0.00). In G1, WOMAC improved: 71.70 to 3.68 and EQVAS 22.25 to 91.55 (P 0.00). In G2, WOMAC deteriorated score worsened from 53.00 to 71.88 and EQVAS 58.60 to 11.96 (P 0.00). DFF and DFE showed coinciding changes. Conclusion: The cause, pathogenesis and treatment are deficient full flexion/deficient full extension; capsular contracture formation and passive flexion or passive extension respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".