Dietary inflammatory index is associated with pain intensity and some components of quality of life in patients with knee osteoarthritis
Bibliographic record
Abstract
Abstract Objectives We aim to measure dietary inflammatory index (DII) and its association with functional status, pain intensity and quality of life (QOL) in patients with knee osteoarthritis (KOA). Dietary information from 220 qualified patients with KOA was collected by a 168-item food frequency questionnaire. The functional status, pain intensity and QOL were evaluated by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire, Visual Analogue Scale (VAS) and SF36 questionnaire respectively. Results Linear regression analysis showed that the DII was significantly associated with VAS (p = 0.040; β = 0.151), and physical function (p = 0.039; β = − 0.184), emotional wellbeing (p = 0.048; β = − 0.158) and pain (p = 0.020; β = 0.161) scales and physical health (p = 0.047; β = 0.110) subscale of QOL after adjusting for age, sex, body mass index, and physical activity. There was no significant differences concerning WOMAC across the DII tertiles with and without adjustment to probable confounders (P trend = 0.091 and 0.181, respectively). After adjustment, a significantly increased severe pain odds was observed in the highest tertile of DII score in comparison with the lowest tertile (OR tertile 3 vs. 1 = 1.55, 95% CI 1.04–2.31; P trend = 0.04).
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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 | 0.001 | 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".