Functional Status in Knee Osteoarthritis and its Relation to Demographic and Clinical Features
Bibliographic record
Abstract
OBJECTIVES: To assess the functional status in a cohort of Iraqi patients with knee Osteoarthritis (OA) and its relation to demographic and clinical features. PATIENTS AND METHODS: This cross-sectional study was conducted on 150 patients with knee OA diagnosed according to the American College of Rheumatology Criteria for classification knee OA. Patients' age, gender, body mass index (BMI), smoking history, educational level, and disease duration were recorded. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score was used to measure functional status of patients with knee OA. RESULTS: . The mean of total WOMAC score was 8.05±2.10 (Range 3-12). The mean WOMAC of: pain score was 3.22 ±0.76 (1-4), stiffness score was 2.05±1.01 and for functional disability score was 2.79±0.88. There was a positive significant correlation between age of the patients and severity of knee OA assessed with total WOMAC score (p=0.026). However, there was a significant negative correlation between educational level and total WOMAC score (p=0.015). CONCLUSIONS: Functional status in knee OA was impaired and there was a statistically positive significant correlation between age of the patients and severity of knee OA with functional impairment. Also, significant negative correlation was demonstrated between educational level and functional impairment.
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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 | 0.002 |
| 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) | 0.002 | 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".