1182-P: Low Socioeconomic Status and Pregnancy Outcomes in Women with Type 2 Diabetes
Bibliographic record
Abstract
Aims: Pregnant women with pre-existing type 2 diabetes have a high rate of social deprivation. Low socioeconomic status (SES) is associated with adverse pregnancy outcomes. Our objective was to assess the association of low SES with adverse pregnancy outcomes in women with type 2 diabetes. Materials and Methods: We conducted an observational cohort study of women in the MiTy trial. Maternal and neonatal outcomes were compared in women with and without low SES. Low SES was described as recent immigration within the previous 5 years, low maternal education or single-parent households. Results: A total of 502 women were included in the MiTy trial. Of the eligible women, 192 (41.60%) met criteria for low SES. Women with low SES had significantly higher HbA1c at 34 weeks gestation (6.18% vs 5.89%, p=<0.01). Low SES was associated with an increase in preterm birth (28.1% vs 19.7%, p=0.05), neonatal hypoglycemia (19% vs 9.8%, p=0.007), and NICU admission >24 hrs (27.2% vs 16.8%, p=0.01). After adjustment for confounders, low SES was associated with an increased risk of an adverse neonatal composite outcome (44.7% vs 31.8%, p=0.007; OR 1.83 (95% CI 1.16-2.92). Of the components of the low SES composite, low maternal education was most strongly associated with the composite neonatal outcome OR 1.71 (95% CI 1.03 - 2.82, p=0.04). Conclusions: In women with type 2 diabetes, low SES was associated with poorer glycemic control and an increased risk of adverse neonatal outcomes. Special attention should be paid to low maternal education as a predictor of adverse outcomes. Disclosure S.Campbell: Speaker's Bureau; Novo Nordisk Canada Inc., HLS Therapeutics Inc. G.Tomlinson: None. D.Feig: Advisory Panel; Novo Nordisk Canada Inc., Speaker's Bureau; Sanofi, Novo Nordisk Canada Inc. Funding Canadian Institutes of Health Research
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".