CAM use among overweight and obese persons with radiographic knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Obesity is associated with knee pain and is an independent predictor of incident knee osteoarthritis (OA); increased pain with movement often leads patients to adopt sedentary lifestyles to avoid pain. Detailed descriptions of pain management strategies by body mass index (BMI) level among OA patients are lacking. The objectives were to describe complementary and alternative medicine (CAM) and conventional medication use by BMI level and identify correlates of CAM use by BMI level. METHODS: Using Osteoarthritis Initiative baseline data, 2,675 patients with radiographic tibiofemoral OA in at least one knee were identified. Use of CAM therapies and conventional medications was determined by interviewers. Potential correlates included SF-12, CES-D, Western Ontario and McMaster Universities Osteoarthritis Index, and Knee injury and Osteoarthritis Outcome Score quality of life. Multinomial logistic regression models adjusting for sociodemographic and clinical factors provided estimates of the association between BMI levels and treatment use; binary logistic regression identified correlates of CAM use. RESULTS: BMI was inversely associated with CAM use (45% users had BMI ≥35 kg/m²; 54% had BMI <25 kg/m²), but positively associated with conventional medication use (54% users had BMI ≥35 kg/m²; 35.1% had BMI <25 kg/m²). Those with BMI ≥30 kg/m² were less likely to use CAM alone or in combination with conventional medications when compared to patients with BMI <25 kg/m². CONCLUSIONS: CAM use is common among people with knee OA but is inversely associated with BMI. Understanding ways to further symptom management in OA among overweight and obese patients is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".