Pregnancy Outcomes in Women With and Without Gestational Diabetes Mellitus According to The International Association of the Diabetes and Pregnancy Study Groups Criteria
Bibliographic record
Abstract
OBJECTIVE: To estimate the incidence of gestational diabetes mellitus (GDM) according to The International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria and the pregnancy complications in women fulfilling these criteria but who are not considered diabetic according to the Canadian Diabetes Association criteria. METHODS: We estimated the rate of GDM according to the IADPSG criteria from November 2008 to October 2010. Then, we conducted a chart review to compare maternal and neonatal outcomes between women classified as GDM according to the IADPSG criteria but not by the Canadian Diabetes Association criteria (group 1; n=186) and nondiabetic women according to both criteria (group 2; n=372). Results were expressed as crude (odds ratio [OR]) or adjusted OR and 95% confidence interval (CI). The study has a statistical power of 80% to detect a difference between 16% and 8% in large for gestational age newborns (α level of 0.05; two-tailed). RESULTS: The rate of GDM using the IADPSG criteria was 27.51% (95% CI 25.92-29.11). Group 1 presented similar rates of large-for-gestational-age newborns (9.1% compared with 5.9%, adjusted OR 1.58, 95% CI 0.79-3.13; P=.19), delivery complications (37.1% compared with 30.1%, OR 1.37, 95% CI 0.95-1.98; P=.10), preeclampsia (6.5% compared with 2.7%, adjusted OR 2.40, 95% CI 0.92-6.27; P=.07), prematurity (6.5% compared with 2.7%, OR 1.10, 95% CI 0.53-2.27; P=.85), neonatal complications at delivery (13.4% compared with 9.7%, OR 1.45, 95% CI 0.84-2.49; P=.20), and metabolic complications (10.8% compared with 14.2%, OR 0.73, 95% CI 0.42-1.26; P=.29) compared with group 2. CONCLUSION: Women classified as nondiabetic by the Canadian Diabetes Association Criteria but considered GDM according to the IADPSG criteria have similar pregnancy outcomes as women without GDM. More randomized studies with cost-effectiveness analyses are needed before implementation of these criteria. LEVEL OF EVIDENCE: II.
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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 | 0.003 |
| 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 | 0.000 |
| 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".