Gestational diabetes and pre‐pregnancy overweight: Possible factors involved in newborn macrosomia
Bibliographic record
Abstract
AIM: Good glycemic control in gestational diabetes mellitus (GDM) seems not to be enough to prevent macrosomia (large-for-gestational-age newborns). In GDM pregnancies we studied the effects of glycemic control (as glycosylated hemoglobin [HbA1c]), pre-pregnancy body mass index (PP-BMI) and gestational weight gain per week (GWG-W) on the frequency of macrosomia. METHODS: We studied 251 GDM pregnancies, divided into two groups: PP-BMI<25.0kg/m(2) (the non-overweight group; n=125), and PP-BMI≥25.0kg/m(2) (the overweight group; n=126). A newborn weight Z-score>1.28 was considered large-for-gestational-age. Statistical analysis was carried out using the Student's t-test and χ(2) -test, receiver-operator characteristic curves and linear and binary logistic regressions. RESULTS: Prevalence of macrosomia was 14.9% among GDM (n=202/251, 88.4%) with good glycemic control (mean HbA1c<6.0%), and 28.1% in those with mean HbA1c≥6.0% (n=49/251, P<0.025). Macrosomia rates were 10.4% in the non-overweight group and 24.6% in the overweight group (P=0.00308), notwithstanding both having similar mean HbA1c (5.48±0.065 and 5.65±0.079%, P=0.269), and similar GWG-W (0.292±0.017 and 0.240±0.021kg/week, P=0.077). Binary logistic regressions showed that PP-BMI (P=0.012) and mean HbA1c (P=0.048), but not GWG-W (P=0.477), explained macrosomia. CONCLUSIONS: Good glycemic control in GDM patients was not enough to reduce macrosomia to acceptable limits (<10% of newborns). PP-BMI and mean HbA1c (but not GWG-W) were significant predictors of macrosomia. Thus, without ceasing in our efforts to improve glycemic control during GDM pregnancies, patients with overweight/obesity need to be treated prior to becoming pregnant.
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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 | 0.005 |
| 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 | 0.001 |
| 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".