Caucasian and Asian difference in role of type 1 diabetes on large-for-gestational-age neonates
Bibliographic record
Abstract
INTRODUCTION: Racial differences in the association between type 1 diabetes mellitus (T1DM) and large-for-gestational-age (LGA) neonates remain unclear. The objective of this study was to compare the effect of T1DM on LGA neonates between Caucasian and Asian women. RESEARCH DESIGN AND METHODS: A population-based retrospective cohort study was conducted among Caucasian and Asian women who had prenatal screening and gave a singleton live birth in an Ontario hospital between April 2015 and March 2018. Multivariable log-binomial regression models were used to estimate the adjusted relative risks (aRRs) and 95% CIs of T1DM on LGA for Caucasian and Asian women. Relative contribution of T1DM to LGA was examined by multivariable logistic regression model, stratified by Caucasian and Asian women. RESULTS: A total of 232 503 women (69.4% Caucasians and 30.6% Asians) were included in the final analysis. The rate of T1DM was higher in Caucasians (0.5%) than in Asians (0.2%), and the rate of LGA neonates was also higher in Caucasians (11.0%) than in Asians (5.0%). The association between T1DM and LGA in Caucasians (aRR 4.18, 95% CI (3.84 to 4.55)) was more robust than that in Asians (aRR 2.11, 95% CI (1.24 to 3.59)). T1DM was the fourth strongest contributor to LGA in Caucasians, while T1DM was the seventh contributor to LGA in Asians. CONCLUSIONS: T1DM plays a more substantial role in LGA among Caucasians than Asians. Clinicians should be aware of the Caucasian-Asian differences of effects of T1DM on LGA when developing pregnancy management strategies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".