Metabolic syndrome is associated with poorer outcomes in people with osteoarthritis participating in a rehabilitation program: an observational study
Bibliographic record
Abstract
Purpose To determine the prevalence of metabolic syndrome and explore its association with clinical outcomes (pain, quality of life, and physical function) in adults participating in an education and exercise program (GLA:D®).Methods An observational study of adults with hip and/or knee osteoarthritis who participated in GLA:D® between 2019 and 2022. Metabolic syndrome status was determined through self-report. Differences in clinical outcomes among people with, at risk of (1–2 risk factors), or without metabolic syndrome were compared at baseline, 3-, and 12-months using linear mixed models (age, sex, and baseline outcomes as covariates).Results Of 6846 participants (aged 65(SD 9) years), 20% (n = 1337) had, and 68% (n = 4632) were at risk of metabolic syndrome. Adults with metabolic syndrome reported higher pain (0–100 VAS: 7.3, 95% CI 5.4–9.1), lower health-related quality of life (EQ5D 0–100, VAS: −8.6, 95% CI −10.2 to −7.0), and slower gait speed (−0.26 m/s, 95%CI -0.3 to −0.23) at baseline compared to those with no metabolic risk factors. Differences remained at 3- and 12-months for pain and quality of life.Conclusions Metabolic syndrome risk factors were common in adults with osteoarthritis. Clinical outcomes remain impaired in people with metabolic syndrome compared to those without after education and exercise, suggesting further intervention may be required.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".