Ovarian markers and irregular menses among women with type 1 diabetes in the Epidemiology of Diabetes Interventions and Complications study
Bibliographic record
Abstract
OBJECTIVE: Women with type 1 diabetes have increased risk of infertility compared to women without diabetes even after adjustment for irregular menses, but aetiologies are incompletely understood. Our aim was to examine the prevalence of abnormalities in ovarian markers consistent with polycystic ovary syndrome in women with type 1 diabetes and associations with irregular menses and diabetes-specific variables. DESIGN, PATIENTS AND MEASUREMENTS: We conducted a secondary analysis of women in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC), a randomized trial and observational follow-up of intensive insulin therapy for type 1 diabetes. We included women with anti-Müllerian hormone (AMH) measurements among women not using oral contraceptives (n = 187). Initial AMH and testosterone measures were performed between EDIC years 1 and 4. History of irregular menses was assessed annually. RESULTS: The median age of women was 35 (interquartile ratio 29, 40) years; 133 (35%) had elevated AMH and 62 (17%) reported irregular menses. Twelve per cent of women had relative elevations in total testosterone. In multivariable models, lower insulin dosages were associated with higher AMH concentrations (P = .0027), but not diabetes duration, glycemic control, body mass index or irregular menses. Neither irregular menses nor diabetes-specific variables were associated with testosterone concentrations. CONCLUSIONS: Among women with type 1 diabetes in their thirties, abnormalities in ovarian markers are common and not associated with irregular menses and thus may partially account for decreased fecundity in women with type 1 diabetes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".