Rates and Risk Factors for Recurrence of Gestational Diabetes
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
OBJECTIVE: To determine the recurrence rate of gestational diabetes (GDM) during a subsequent pregnancy among women who had GDM during an index pregnancy and to identify factors associated with the probability of recurrence RESEARCH DESIGN AND METHODS: A retrospective longitudinal study was performed in Nova Scotia, Canada, of women who were diagnosed as having GDM during a pregnancy between the years of 1980 and 1996 and who had at least one subsequent pregnancy during this time period. When only the index and first subsequent pregnancy were analyzed, the cohort included 651 women. The recurrence rate of GDM in the pregnancy after the pregnancy with the initial diagnosis of GDM was determined. Multivariate regression models were constructed to model the recurrence of GDM in a subsequent pregnancy as functions of potential predictors to estimate RRs and CIs. RESULTS: The rate of recurrence of GDM in the pregnancy subsequent to the index pregnancy was found to the 35.6% (95% CI = 31.9-39.3%). Multivariate regression models showed that infant birth weight in the index pregnancy and maternal prepregnancy weight before the subsequent pregnancy were predictive of recurrent GDM. CONCLUSIONS: In this large cohort of women, slightly more than one-third of the subjects had diabetes in a subsequent pregnancy, which is consistent with recurrence rates in other predominately white populations. Strategies to reduce the occurrence of neonatal macrosomia and maternal prepregnancy obesity may help lower the rate of recurrence of GDM.
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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 | 0.001 |
| 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) | 0.000 | 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