Healthy eating index and risk of diminished ovarian reserve: a case–control study
Bibliographic record
Abstract
Diminished ovarian reserve (DOR) is associated with reduced fertility and poor reproductive outcomes. The association between dietary patterns and DOR was not well studied. The purpose of this study was to evaluate the relationship between adhering to the healthy eating index (HEI-2015) and the risk of DOR. In this case-control study, 370 Iranian women (120 with DOR and 250 age- and BMI-matched controls) were examined. A reliable semi-quantitative food frequency questionnaire was used to collect diet-related data. We analyzed the HEI-2015 and their dietary intake data to determine major dietary patterns. The multivariable logistic regression was used in order to analyze the association between HEI-2015 and risk of DOR. We found no significant association between HEI-2015 score and risk of DOR in the unadjusted model (OR 0.78; 95%CI 0.59, 1.03). After controlling for physical activity and energy intake, we observed that women in the highest quartile of the HEI-2015 score had 31% decreased odds of DOR (OR 0.69; 95%CI 0.46, 0.93). This association remained significant even after adjusting for all potential confounders. Overall, increased adherence to HEI may lead to a significant reduction in the odds ratio of DOR. Clinical trials and prospective studies are needed to confirm this association.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".