Is There a Dose‐Response Relationship Between Weight Loss and Symptom Improvement in Persons With Knee Osteoarthritis?
Bibliographic record
Abstract
OBJECTIVE: We examined the dose-response relationship between weight reduction and pain/functional improvement in persons with symptomatic knee osteoarthritis (KOA) participating in a community-based weight loss program. METHODS: Consecutive participants with KOA and enrolled in the 18-week Osteoarthritis Healthy Weight for Life weight-loss program were selected. In this completer-type analysis, participants were assessed at baseline, 6 weeks, and 18 weeks for body weight and Knee Injury and Osteoarthritis Outcome Score (KOOS) subscales. The dose-response relationship between weight-change categories (>10%, 7.6-10%, 5.1-7.5%, 2.6-5.0%, and <2.5% of body weight loss) and change in KOOS scores was assessed by repeated-measures analysis of variance, controlling for sex and age, body mass index (BMI), and KOOS. The Western Ontario McMaster Universities Osteoarthritis Index function score derived from the KOOS was used to assess a meaningful clinical functional improvement. RESULTS: A total of 1,383 persons (71% females) were enrolled. Mean ± SD age, height, and weight were 64 ± 8.7 years, 1.66 ± 0.09 meters, and 95.1 ± 17.2 kg, respectively. Mean ± SD BMI was 34.4 ± 5.2 kg/m(2) with 82% of participants obese at baseline. A total of 1,304 persons (94%) achieved a >2.5% reduction in body weight. There was a significant dose-response relationship between all KOOS subscales and percentage of weight change across all weight-change categories. Participants required ≥7.7% (95% confidence interval 5.2, 13.3) body weight loss to achieve a minimal clinically important improvement in function. CONCLUSION: There is a significant dose-response relationship between percentage of weight loss and symptomatic improvement. This study confirms the feasibility of weight loss as a therapeutic intervention in KOA in a community-based setting.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".