Modified Therapy for Gestational Diabetes Using High-Risk and Low-Risk Fetal Abdominal Circumference Growth to Select Strict Versus Relaxed Maternal Glycemic Targets
Bibliographic record
Abstract
The traditional treatment goal for ges-tational diabetes mellitus (GDM)has been to achieve “normal ” range values for maternal glucose by diet and or insulin therapy, adapting a strategy suc-cessful in treating pregestational diabetes during pregnancy. Intensive insulin ther-apy to achieve strict euglycemia in GDM pregnancies has improved perinatal mor-bidity; however, it has not eliminated the excess rate of macrosomia compared with the reference populations (1). Increasing evidence suggests that disturbances in the intrauterine metabolic environment pro-duced by GDM appear to increase the risk in offspring for obesity and diabetes. The obesity risk in early childhood in off-spring born to mothers with GDM has been correlated with the birth weight and parental obesity, and those children who were large-for-gestational-age (LGA) at birth had obesity rates close to 40 % com-pared with 25 % in those born with nor-mal weight (2). Studies that have attempted to reduce macrosomia rates by setting very strict glycemic targets during pregnancy have required insulin therapy in two-thirds of the women (3). However, only a minority of offspring of GDM mothers appear to be at risk for fetal over-growth and newborn morbidity, even when GDM is untreated in blinded con-trolled trials (4,5). The Toronto Tri-Hospital Gestational Diabetes Project demonstrated a modest association of newborn morbidity with antenatal mater-nal glucose concentrations, adjusting for other risk factors (6). However, no threshold values that would suggest treat-ment were found. These facts led Buchanan et al. (7) to advocate using fetal ultrasound measure-ments of growth in addition to maternal glycemia to identify which fetuses in utero are at increased and decreased risk for complications. This approach relaxes glycemic targets in women whose fetuses are at low risk for LGA growth and inten-sifies therapy by using stricter glycemic targets for those at high risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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".