Dysglycemia and a History of Reproductive Risk Factors
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to identify reproductive risk factors associated with dysglycemia (diabetes, impaired glucose tolerance, and impaired fasting glucose) in a contemporary multiethnic population. RESEARCH DESIGN AND METHODS: We studied 14,661 women screened with an oral glucose tolerance test for the Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication (DREAM) trial. Reproductive risk factors were compared in normoglycemic and dysglycemic women. RESULTS: Dysglycemia was significantly associated with the number of children born (odds ratio 1.03 per child [95% CI 1.01-1.05]), age (1.05 per year [1.04-1.05]), non-European ancestry (1.09 [1.01-1.17]), preeclampsia/eclampsia (1.14 [1.02-1.27]), irregular periods (1.21 [1.07-1.36]), and gestational diabetes mellitus (GDM) (1.53 [1.35-1.74]). The relationship between GDM and dysglycemia did not differ across BMI tertiles (P = 0.84) nor did the relationships of other risk factors. CONCLUSIONS: Reproductive factors, particularly GDM, are associated with dysglycemia in middle-aged women from many ethnicities. Reproductive factors can be used to counsel young women about their future risk of dysglycemia, whereas in middle age they may help screen for dysglycemia.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".