Diagnostic thresholds for gestational diabetes and their impact on pregnancy outcomes: a systematic review
Bibliographic record
Abstract
AIMS: To assess different diagnostic thresholds for gestational diabetes on outcomes for mothers and their offspring in the absence of treatment for gestational diabetes. This information was used to inform a National Institutes of Health consensus conference on diagnosing gestational diabetes. METHODS: We searched 15 electronic databases from 1995 to May 2012. Study selection was conducted independently by two reviewers. Randomized controlled trials or cohort studies were eligible if they involved women without known pre-existing diabetes mellitus and who did not undergo treatment for gestational diabetes. One reviewer extracted, and a second reviewer verified, data for accuracy. Two reviewers independently assessed methodological quality. RESULTS: Thirty-eight studies were included. Three large, methodologically strong studies showed a continuous positive relationship between increasing glucose levels and the incidence of Caesarean section and macrosomia. When data were examined categorically (i.e. women meeting or not meeting specific diagnostic thresholds), women with gestational diabetes across all glucose criteria had significantly more Caesarean sections, shoulder dystocia, macrosomia (except for International Association of Diabetes in Pregnancy Study Groups' criteria) and large for gestational age. Higher glucose thresholds did not consistently demonstrate greater risk for all outcomes. CONCLUSIONS: Higher glucose thresholds did not consistently demonstrate greater risk, possibly because studies did not compare mutually exclusive groups of women. A pragmatic approach for diagnosis of gestational diabetes using Hyperglycemia and Adverse Pregnancy Outcome Study odds ratio 2.0 thresholds warrants further consideration until additional analysis of the data comparing mutually exclusive groups of women is provided and large randomized controlled trials investigating different diagnostic and treatment thresholds are completed.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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".