Mediterranean diet adherence and risk of multiple sclerosis: a case-control study.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We conducted a hospital-based, case-control study to examine the association between Mediterranean diet (MD) and the risk of multiple sclerosis (MS) in Iran. METHODS AND STUDY DESIGN: A total of 70 patients with MS and 142 controls underwent face-to-face interviews in the major neurological clinics of Tehran, Iran. Adherence to a MD was assessed using the 9-unit dietary score, to evaluate the level of conformity of the individual's diet to the Mediterranean dietary pattern. Multivariate logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Higher consumption of fruits (OR=0.28, 95% CI: 0.12-0.63, p-value: 0.002) and vegetables (OR=0.23, 95% CI: 0.10-0.53, p-value: 0.001) were significantly associated with reduced MS risk. In both age adjusted and multivariate adjusted model, the OR of MS decreased significantly in the third as compared to the first tertile of MD score (age adjusted OR: 0.21, 95% CI: 0.06-0.67; p-trend: 0.01, Multivariate adjusted OR: 0.23, 95% CI: 0.06-0.89, p-trend: 0.04). CONCLUSIONS: Our study suggests that a high quality diet assessed by MD may decrease the risk of MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".