Decreased urine albumin:creatinine ratios in infants of diabetic mothers: does exposure to diabetic pregnancies alter fetal renal development?
Bibliographic record
Abstract
Offspring of diabetic mothers experience an increased risk for type 2 diabetes but it is not known whether diabetic pregnancies also confer a higher inter-generational risk for diabetic complications. Because microalbuminuria is a sensitive indicator of glomerular damage, we compared the urine albumin:creatinine ratios (ACRs) between 65 infants of diabetic mothers (InfDM+) and 59 infants of non-diabetic mothers (InfDM-), and repeated the comparisons in 21 InfDM+ and 19 InfDM- when children were 5-19 months old. ACRs were higher among neonates compared with normal reference values for adults, but declined with increasing age. The only independent predictor of higher ACRs in a logistic regression model (⩾13 mg/mmol v. <13 mg/mmol) was the presence of delivery complications (odds ratio 2.95; P = 0.015). Neither high nor low birth weight was associated with higher neonatal ACRs. The most unique finding of the study was that InfDM+ had significantly lower ACRs than InfDM- [mean = 12.9 (median = 6.0) v. mean = 16.6 (median = 11.5), respectively at P = 0.05] even after adjusting for other variables using logistic regression (odds ratio 0.25; P = 0.001). In contrast, by 5-19 months, there was a trend toward higher ACRs among InfDM+ compared with InfDM- [mean = 6.3 mg/mmol (median = 1.9) v. mean = 3.0 mg/mmol (median = 2.5), respectively at P = 0.25]. Lower ACRs in InfDM+ may be due to developmental changes in fetal kidneys induced by hyperinsulinemia. Although the implications of this observation are unclear, it is possible that exposure to a diabetic intrauterine environment might influence the later risk for renal disease.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".