Gestational diabetes mellitus and retinal microvasculature
Bibliographic record
Abstract
BACKGROUND: Small-vessel dysfunction may be an important consequence of chronic hyperglycemia. We examined the association between gestational diabetes mellitus (GDM), a state of transient hyperglycemia during pregnancy, and retinal microvascular changes in pregnant women at 26-28 weeks of pregnancy. METHODS: A total of 1136 pregnant women with singleton pregnancies were recruited during their first trimester at two major Singapore maternity hospitals in an on-going birth cohort study. Participants underwent an oral glucose tolerance test and retinal imaging at 26-28 weeks gestation (n = 542). We used the 1999 World Health Organization (WHO) criteria to define GDM: ≥7.0 mmol/L for fasting glucose and/or ≥7.8 mmol/L for 2-h post-glucose. Retinal microvasculature was measured using computer software (Singapore I Vessel Analyzer, SIVA version 3.0, Singapore Eye Research Institute, Singapore) from the retinal photographs. RESULTS: In a multiple linear regression model adjusting for age, ethnicity and maternal education, mothers with GDM had narrower arteriolar caliber (-1.6 μm; 95% Confidence Interval [CI]: -3.1 μm, -0.2 μm), reduced arteriolar fractal dimension (-0.01 Df; 95% CI: -0.02 Df, -0.001 Df;), and larger arteriolar branching angle (1.8°; 95% CI: 0.3°, 3.3°) than mothers without GDM. After further adjusting for traditional risks of GDM, arteriolar branching angle remained significantly larger in mothers with GDM than those without GDM (2.0°; 95% CI: 0.5°, 3.6°). CONCLUSIONS: GDM was associated with a series of retinal arteriolar abnormalities, including narrower caliber, reduced fractal dimension and larger branching angle, suggesting that transient hyperglycemia during pregnancy may cause small-vessel dysfunction.
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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 | 0.000 | 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) | 0.001 | 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".