Comparative analysis of current diagnostic criteria for gestational diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: To compare current guidelines for diagnosis of gestational diabetes mellitus (GDM) and to identify the ones that are the most relevant for application among pregnant Bulgarian population. METHODS: A total of 800 pregnant women at high risk for GDM underwent 75 g oral glucose tolerance test between 24 and 28 weeks of gestation as antenatal screening. The results were interpreted and classified according to the guidelines of the International Association of Diabetes and Pregnancy Study Groups (IADPSG), American Diabetes Association (ADA), Australasian Diabetes in Pregnancy Society, Canadian Diabetes Association, European Association for the Study of Diabetes, New Zealand Society for the study of Diabetes and World Health Organization. RESULTS: The application of different diagnostic criteria resulted in prevalences of GDM between 10.8% and 31.6%. Using any two sets of criteria, women who were classified differently varied between 0.1% and 21.1% (P < 0.001).The IADPSG criteria were the most inclusive criteria and resulted in the highest prevalence of GDM. There was a significant difference in the major metabolic parameters between GDM and control groups, regardless of which of the diagnostic criteria applied. GDM diagnosed according to all criteria resulted in increased proportion of delivery by caesarean section (CS). However, only ADA and IADPSG criteria identified both increased macrosomia (odds ratio, 2.36; 2.29) and CS rate. CONCLUSION: The need for GDM screening is indisputable. In our view, the new IADPSG guidelines offer a unique opportunity for a unified national and global approach to GDM.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".