Low intakes of dietary fiber and magnesium are associated with insulin resistance and hyperandrogenism in polycystic ovary syndrome: A cohort study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Women with polycystic ovary syndrome (PCOS) often have insulin resistance (IR) which may be worsened by obesity. The roles of dietary intake and activity are unclear. Our objectives were to determine whether (a) high caloric intake or inactivity explains obesity in PCOS, and (b) dietary composition is associated with PCOS phenotypes. METHODS: Eighty-seven women with PCOS and 50 women without PCOS participated in this cohort study at a reproductive medicine center. Data collected included 3-day food and physical activity records, anthropometrics, and metabolic and hormonal assays. RESULTS: Women with PCOS had increased body mass index (BMI) but similar caloric intake and activity to women without PCOS. There were no differences in protein, carbohydrates, fat, or glycemic load consumption, but women with PCOS consumed less fiber (medians: 19.6 vs. 24.7 g) and less magnesium (medians: 238.9 vs. 273.9 mg). In women with PCOS, those with IR consumed less fiber, less magnesium, and greater glycemic load than those without IR (medians: 18.2 vs. 22.1 g, 208.4 vs. 264.5 mg, 89.6 vs. 83.5). Fiber intake of women with PCOS was negatively correlated with IR, fasting insulin, glucose tolerance, testosterone, and dehydroepiandrosterone sulfate. Magnesium intake was negatively correlated with IR, C-reactive protein, and testosterone, but positively correlated with HDL cholesterol. Fiber intake and BMI accounted for 54.0% of the variance observed in IR. CONCLUSIONS: Obesity in women with PCOS could not be explained by overeating or inactivity. Increasing dietary fiber and magnesium intakes may assist in reducing IR and hyperandrogenemia in women with PCOS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it