Effect of maternal weight, adipokines, glucose intolerance and lipids on infant birth weight among women without gestational diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: The delivery of excess maternal nutrients to the fetus is known to increase the risk of macrosomia, even among infants of women without gestational diabetes mellitus. With the current obesity epidemic, maternal adiposity and its associated effects on circulating adipokines and inflammatory proteins may now have a greater impact on fetal growth. We sought to evaluate the independent effects of maternal glycemia, lipids, obesity, adipokines and inflammation on infant birth weight. METHODS: We included 472 women who underwent an oral glucose tolerance test in late pregnancy and were found not to have gestational diabetes; 104 (22.0%) had gestational impaired glucose tolerance. We also measured fasting levels of insulin, low-and high-density lipoprotein cholesterol, triglycerides, leptin, adiponectin and C-reactive protein. Obstetric outcomes were assessed at delivery. RESULTS: The mean birth weight was 3481 g (standard deviation 493 g); 68 of the infants were large for gestational age. On multiple linear regression analysis, positive determinants of birth weight were length of gestation, male infant, weight gain during pregnancy up to the time of the oral glucose tolerance test, body mass index (BMI) before pregnancy and impaired glucose tolerance in pregnancy. Leptin, adiponectin and C-reactive protein levels were each negatively associated with birth weight. On logistic regression analysis, the significant metabolic predictors of having a large-for-gestational-age infant were BMI before pregnancy (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.05-1.27, per 1 kg/m(2) increase), weight gain during pregnancy up to the time of the oral glucose tolerance test (OR 1.12, 95% CI 1.05-1.19, per 1 kg increase) and leptin level (OR 0.50, 95% CI 0.30-0.82, per 1 standard deviation change). INTERPRETATION: Among women without gestational diabetes, maternal adiposity and leptin levels were the strongest metabolic determinants of having a large-for-gestational-age infant rather than glucose intolerance and lipid levels.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".