Maternal obesity and familial history of diabetes have opposing effects on infant birth weight in women with mild glucose intolerance in pregnancy
Bibliographic record
Abstract
Phillip Segala, Jill K. Hamiltonb, Mathew Sermerc, Philip W. Connellyad, Anthony J. G. Hanleyaefg, Bernard Zinmanafg & Dr Ravi Retnakaranafg*a Department of Medicine, University of Toronto, Toronto, Canadab Division of Endocrinology, Hospital for Sick Children, Toronto, Canadac Division of Obstetrics and Gynecology, Mount Sinai Hospital, Toronto, Canadad Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canadae Department of Nutritional Sciences, University of Toronto, Toronto, Canadaf Division of Endocrinology, University of Toronto, Toronto, Canadag Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada† Correspondence: DrRavi Retnakaran, Leadership Sinai Centre for Diabetes, 60 Murray Street, Suite L5-039, Mailbox 21, Toronto, ON, Canada, M5T3L9, +1 416 586 4800 ext. 3941, +1 416 586 8853 rretnakaran@mtsinai.on.caObjective. Pregnant women with an abnormal screening glucose challenge test (GCT) but without gestational diabetes mellitus (GDM) on subsequent oral glucose tolerance test (OGTT) are at increased risk of delivering macrosomic and large for gestational age (LGA) neonates. We thus sought to evaluate the maternal constitutional and biochemical factors that determine infant birth weight in this patient population.Methods. Women with an abnormal GCT were evaluated at the time of their OGTT in late pregnancy. This analysis was restricted to Caucasian women without GDM (N = 86). Maternal demographic and biochemical factors were evaluated in relation to infant birth weight and LGA.Results. After adjustment for length of gestation, birth weight was positively associated with pre-pregnancy body mass index (BMI) (r = 0.31, p = 0.0063) and negatively correlated with maternal serum levels of the insulin-sensitizing protein adiponectin (r = −0.30, p = 0.0084). On multiple linear regression analysis, pre-pregnancy BMI and weight gain in pregnancy were positive independent determinants of infant birth weight, while family history of diabetes emerged as a negative independent correlate. Logistic regression analysis confirmed that pre-pregnancy BMI was a positive predictor of LGA (odds ratio (OR) = 1.25, 95% confidence interval (CI) 1.05–1.49), whereas family history of diabetes was again identified as a negative determinant (OR = 0.10, 95% CI 0.02–0.59). In contrast, neither measures of glycemia nor insulin resistance/sensitivity were independently associated with birth weight or LGA.Conclusion. In pregnant women with an abnormal GCT but without GDM, pre-gravid maternal obesity predicts increased infant birth weight, whereas family history of diabetes is independently associated with decreased infant size.
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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".