The association between socio‐demographic marginalization and plasma glucose levels at diagnosis of gestational diabetes
Bibliographic record
Abstract
AIMS: We examined the association between socio-demographic marginalization and plasma glucose levels at diagnosis of gestational diabetes in a multi-ethnic and socio-economically diverse patient group. METHODS: Medical charts at a Toronto gestational diabetes clinic were reviewed for women with a recorded pregnancy between 1 March 2006 and 26 April 2011. One-hour 50-g glucose challenge test values and postal code data were abstracted. Postal codes were merged with 2006 Canadian census data to compute neighbourhood-level ethnic concentration (% recent immigrants, % visible minorities) and material deprivation (% low education, % low income, single-parent households). We compared women in the highest neighbourhood quintiles for both ethnic concentration and material deprivation with all other women to explore an association between marginalization and diagnostic glucose levels. Multivariate regression models of glucose challenge test values and insulin prescription were adjusted for age, prior gestational diabetes, parity and diabetes family history. RESULTS: Among 531 patients with complete glucose challenge test data (mean 11.94 mmol/l, sd 1.83), those in the most marginalized neighbourhoods had 0.43 mmol/l higher glucose challenge test values (95% CI 0.08-0.78) compared with the rest of the study population. Other factors associated with higher glucose challenge test values were prior gestational diabetes (0.59 mmol/l increment, 95% CI 0.19-0.99) and diabetes family history (0.32 mmol/l increment, 95% CI -0.01 to 0.66). Each additional 1 mmol/l glucose challenge test result was associated with an increased likelihood of being prescribed insulin (odds ratio 1.33, 95% CI 1.17-1.51). CONCLUSIONS: Women living in the most materially deprived and ethnically concentrated neighbourhoods have higher glucose levels at diagnosis of gestational diabetes. They may need close monitoring for timely initiation of insulin.
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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 | 0.002 | 0.003 |
| 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 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".