Associated Factors with Pain and Disability in Patients With Knee Osteoarthritis
Bibliographic record
Abstract
Objective: To assess factors associated with pain and functional level in patients with knee osteoarthritis (OA). Materials and Methods: Patients with knee OA (n=161), with a mean age of 62.4± 8.7 yrs were studied. Age, sex, body mass index (BMI), education level, smoking habit, regular physical activity habit, symptom duration were recorded. Kellgren-Lawrence scores were calculated in anterio-posterior and lateral knee radiographs. Functional level of patients were assessed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and pain severity of the patients were assessed by Visual Analoge Scale (VAS). Results: The BMI was positively correlated with mean scores of WOMAC pain, joint stiffness and daily living activities subscores (r=0.592, r=0.634, and r=0.749, respectively). Education level was inversely correlated with mean scores of WOMAC pain, joint stiffness and daily living activities subscores (r=-0.394, r=-0.345, and r=-0.352, respectively). Kellgren-Lawrence scores of anterior-posterior and lateral view radiographs were found to be correlated with age and symptom duration (r=0,263, p=0,001 and r=0,339, p=0,016, respectively). No relationship was found between pain VAS scores and any assessed factors.When WOMAC subscale scores and VAS scores were compared according to gender, WOMAC pain scores were found higher in females (p=0.024). No correlation was found between remainder factors and scores of the three sections of WOMAC. Conclusion: The BMI is the most important factor associated with functional level and pain severity of patients with KOA. Patients must be encouraged to loose weight in order to decrease symptom and disease severity. (Turk J Rheumatol 2010; 25: 77-81)
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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 | 0.000 | 0.003 |
| 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".