Clinical, <scp>Health‐Related</scp> Quality of Life, and Gait Differences Among Obesity Classes in Adults With Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine whether clinical, health-related quality of life (HRQL), and gait characteristics in adults with knee osteoarthritis (OA) differed by obesity category. METHODS: This cross-sectional analysis of 823 older adults (mean age 64.6 years, SD 7.8 years) with knee OA and overweight or obesity compared clinical, HRQL, and gait outcomes among obesity classifications (overweight or class I, body mass index [BMI] 27.0-34.9; class II, BMI 35.0-39.9; class III BMI ≥40.0). RESULTS: Patients with class III obesity had worse Western Ontario McMasters Universities Arthritis Index knee pain (0-20) than the overweight or class I (mean 8.6 vs 7.0; difference 1.5; 95% confidence interval [CI] 1.0-2.1; P < 0.0001) and class II (mean 8.6 vs 7.4; difference 1.1; 95% CI 0.6-1.7; P = 0.0002) obesity groups. The Short Form 36 physical HRQL measure was lower in the class III obesity group compared to the overweight or class I (mean 31.0 vs 37.3; difference -6.2; 95% CI -7.8 to -4.7; P < 0.0001) and class II (mean 31.0 vs 35.0; difference -3.9; 95% CI -5.6 to -2.2; P < 0.0001) obesity groups. The class III obesity group had a base of support (cm) during gait that was wider than that for the overweight or class I (mean 14.0 vs 11.6; difference 3.3; 95% CI 2.6-4.0; P < 0.0001) and class II (mean 14.0 vs 11.6; difference 2.4; 95% CI 1.6-3.2; P < 0.0001) obesity groups. CONCLUSION: Among adults with knee OA, those with class III obesity had significantly higher pain levels and worse physical HRQL and gait characteristics compared to adults with overweight or class I or class II obesity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".