Controversies around gestational diabetes. Practical information for family doctors.
Bibliographic record
Abstract
OBJECTIVE: To summarize some of the issues facing primary care physicians who are seeing increasing numbers of patients with gestational diabetes mellitus (GDM) and to explore new developments in use of oral hypoglycemics during pregnancy. QUALITY OF EVIDENCE: All the literature on screening for GDM offers level III evidence. Much of the literature on treatment is also level III, but newer studies offer level I evidence and are more useful for daily practice. Existing research leaves many important questions unanswered; research findings are inconsistent among studies, and treatment strategies are challenging to implement. MAIN MESSAGE: Recent studies have clarified that rates of neonatal mortality and congenital malformations are not higher among the offspring of mothers with GDM. Treatment might affect birth weight, but whether treatment is associated with reductions in rates of shoulder dystocia and cesarean section is unclear. Several level I studies conclude that the oral hypoglycemic glyburide can be used safely and effectively during the second and third trimesters of pregnancy. CONCLUSION: Management of GDM remains a controversial area in obstetric care. It is a growing area of research, and new developments that might clarify risk and simplify treatment are expected in the coming years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.015 | 0.011 |
| Insufficient payload (model declined to judge) | 0.081 | 0.027 |
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".