Inflammatory markers and physical function among older adults with knee osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: To investigate whether serum concentrations of various inflammatory markers are associated with physical function and disease severity among older obese adults with knee osteoarthritis (OA). METHODS: Data are from baseline assessments in 274 patients with knee OA participating in an exercise and nutrition intervention study. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) was used to assess self-reported physical function, pain, and stiffness. The presence of disability was assessed, walking speed was calculated on the basis of the 6-minute walk test, and knee radiographs determined the radiographic severity of OA. Serum concentration of interleukin 6 (IL-6), C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-alpha), and the soluble receptors IL-6sR, IL-2sR, TNF-sR1 and TNF-sR2 were measured by ELISA. RESULTS: In multivariate regression analyses adjusted for age, sex, race, body mass index, comorbid conditions, and use of nonsteroid antiinflammatory drugs, higher serum levels of TNF-sR1 and TNF-sR2 were significantly associated with lower scores on the WOMAC physical function, with more symptoms of pain and stiffness, and with more reported physical disability. In addition, higher serum levels of TNF-sR1 and TNF-sR2 were significantly associated with slower walking speed, and tended to be associated with worse radiographic scores. Higher serum levels of IL-6 tended to be associated with slower walking speed, but no significant associations were observed for CRP, IL-6sR, or IL-2sR. CONCLUSION: Especially high levels of the soluble receptors of TNF-alpha were found to be associated with lower physical function, increased OA symptoms, and worse knee radiographic scores in older obese adults with knee OA.
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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 | 0.001 |
| 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 | 0.000 |
| 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".