Diet quality is associated with pain intensity and quality of life in a sample of patients with knee osteoarthritis: a cross-sectional study
Bibliographic record
Abstract
Introduction: Knee osteoarthritis (KOA) is the most common degenerative joint disease resulting in bone pain and disability. The aim of current study is to determine diet quality by healthy eating index (HEI)-2015 in association with pain and functional status among a sample of participants with primary knee OA. Methods: In this cross-sectional study, 220 patients with knee OA were recruited via convenience sampling in the outpatient clinics of Tabriz University of Medical Sciences between April and September 2018. The HEI-2015 score was calculated from dietary data collected using a Food Frequency Questionnaire (FFQ). Visual analogue scale, Western Ontario and McMaster Universities Osteoarthritis Index and the SF36 quality of life (QoL) questionnaire were applied to measure the pain intensity, functional status and QoL in the participants, respectively. Participants were categorized based on the quintile cutoff points of HEI score including 42-62, 63-69, 70-75, 76-78 and 79-100. Results: The mean score of HEI was 70.62±10.18 (range: 42–89). Participants with greater HEI- 2015 scores had higher total energy intake (P=0.008) and greater dietary intake of carbohydrates (P=0.01), protein (P=0.009), monounsaturated fatty acids (P=0.01), polyunsaturated fatty acids (P=0.007) and fiber (P=0.009) and lower intake of saturated fatty acids (P=0.005). Participants in higher quintiles of HEI had significantly lower pain intensity (P=0.001) and higher scores of physical function (P=0.001), pain (P=0.001) and role limitation due to physical problems (P=0.005) subscales of SF-36 QoL questionnaire in comparison with participants in lower quintiles of HEI-2015. Conclusion: The HEI-2015 score is associated with pain intensity and two domain of QoL in patients 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".