The Influence of Obesity on Pain and Function in Knee Osteoarthritis: Comparison of Body Mass Index With Seven Knee Function Scales and Two Pain Scales
Bibliographic record
Abstract
INSTRUCTION: Obesity is a health problem that is rapidly increasing both in local societies and internationally. It is well known that obesity has a risk relationship with many different diseases. The scale for obesity is Body Mass Index (BMI), which has been widely accepted worldwide for many years. The relationship between BMI and disease is a frequently studied topic. This study aimed to evaluate and measure knee function and pain in patients with knee osteoarthritis. MATERIALS AND METHODS: A total of 100 patients in radiologically advanced stage (Kellgren/Lawrence grade 3-4) who were scheduled for knee arthroplasty were administered seven knee osteoarthritis scales (Timed up and Go (TUG), American Knee Society Score (AKSS), the Lequesne Knee Index, Knee injury and Outcome Subtotal Pain Score (KOOS-PS), Western Ontario and McMaster Universities Index (WOMAC), Oxford Knee Score, and International Knee Documentation Committee (IKDC)), and two pain scales, the McGill Pain Questionnaire and a visual analog pain scale (VAS), which were completed simultaneously on the same form. Data that did not show a normal distribution were analyzed with Spearman and Kendall correlation tests. RESULTS: The mean age of the 100 consecutive patients, 92% of whom were female, was 65.2 years (48-81 years). There was a strong correlation between BMI and all functional knee scales, but no significant association was found between pain scales and BMI. CONCLUSION: In our hypothesis, we expected that all functional and pain scales would moderately or strongly correlate with BMI. However, while a strong correlation with the functional pain scales is an expected result, the expected strong positive correlation between pain scales and BMI was not found in the study.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".