Missed antenatal diabetes care appointments and neonatal outcomes for pregnancies with Type 1 and Type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: There is limited information regarding the association between missed appointments and neonatal outcomes for diabetes in pregnancy. STUDY METHODS: This retrospective live birth cohort included pregnant women with Type 1 or 2 diabetes who attended specialized clinics from 2008 to 2020. The association between at least one missed antenatal diabetes appointments and outcomes were assessed using logistic regression and reported as adjusted odds ratios (aOR) (95% confidence interval). Mediation analyses were conducted to examine if above target HbA1c mediated these relationships. RESULTS: The cohort included 407 and 902 women with Type 1 and 2 diabetes, respectively, of whom 25.1% and 34.5% missed at least one appointment. Women with Type 1 diabetes who missed an appointment were more likely to have a caesarean section (aOR 1.95 [1.15, 3.31]) and their babies more likely to be admitted to the neonatal intensive care unit (aOR 2.25 [1.35, 3.75]). Women with Type 2 diabetes who missed an appointment were more likely to have a large-for-gestational-age infant (aOR 1.61 [1.13, 2.28]), and an extreme large-for-gestational-age infant (aOR 1.69 [1.02, 2.81]) compared with women who did not miss appointments. Above target HbA1c mediated the relationship between missed appointments and caesarean delivery in Type 1 diabetes and large-for-gestational age and extreme large-for-gestational age in Type 2 diabetes. CONCLUSION: In individuals with Type 1 and 2 diabetes, there are differences in neonatal outcomes between those who missed an appointment compared to those who did not. It remains unclear if missed diabetes appointments are causative or a marker of other health behaviours or risk factors leading to neonatal morbidity.
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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 | 0.000 | 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 | 0.001 | 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".