Dietary glycaemic index and glycaemic load and upper gastrointestinal disorders: results from the <scp>SEPAHAN</scp> study
Bibliographic record
Abstract
BACKGROUND: Little is known about the effects of carbohydrate, particularly any association between dietary glycaemic index or glycaemic load and uninvestigated heartburn or uninvestigated chronic dyspepsia in the community. The present study aimed to determine associations between dietary glycaemic index or glycaemic load and uninvestigated heartburn or uninvestigated chronic dyspepsia. METHODS: This cross-sectional study was conducted in 2987 adults. Dietary glycaemic index and glycaemic load were estimated using a validated food-frequency questionnaire. Uninvestigated heartburn and uninvestigated chronic dyspepsia were determined using a modified and validated version of the Rome III questionnaire. RESULTS: After controlling for various confounders, high glycaemic load was associated with an increased risk of uninvestigated heartburn [odds ration (OR) = 1.75; 95% confidence interval CI = 1.03, 2.97; P = 0.04] and uninvestigated chronic dyspepsia (OR = 2.14; 95% CI: 1.04, 4.37; P = 0.04) in men but not in women. In normal-weight individuals, high glycaemic index was related to an increased risk of uninvestigated heartburn (OR = 1.52; 95% CI: 1.07, 2.15; P = 0.02) and high glycaemic load to an increased risk of uninvestigated chronic dyspepsia (OR=1.78; 95% CI: 1.05, 3.01; P = 0.03). No significant associations were observed in subjects with excess body weight. CONCLUSIONS: Our data suggest that there are body mass index- and sex-specific associations between dietary carbohydrate quality with uninvestigated heartburn and uninvestigated chronic dyspepsia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".