Screening Tests for Gestational Diabetes: A Systematic Review for the U.S. Preventive Services Task Force
Bibliographic record
Abstract
BACKGROUND: A 50-g oral glucose challenge test (OGCT) is a widely accepted screening method for gestational diabetes mellitus (GDM), but other options are being considered. PURPOSE: To systematically review the test characteristics of various screening methods for GDM across a range of recommended diagnostic glucose thresholds. DATA SOURCES: 15 electronic databases from 1995 to May 2012, reference lists, Web sites of relevant organizations, and gray literature. STUDY SELECTION: Two reviewers independently identified English-language prospective studies that compared any screening test for GDM with any reference standard. DATA EXTRACTION: One reviewer extracted and a second reviewer verified data from 51 cohort studies. Two reviewers independently assessed methodological quality. DATA SYNTHESIS: The sensitivity, specificity, and positive and negative likelihood ratios for the OGCT at a threshold of 7.8 mmol/L (140 mg/dL) were 70% to 88%, 69% to 89%, 2.6 to 6.5, and 0.16 to 0.33, respectively. At a threshold of 7.2 mmol/L (130 mg/dL), the test characteristics were 88% to 99%, 66% to 77%, 2.7 to 4.2, and 0.02 to 0.14, respectively. For a fasting plasma glucose threshold of 4.7 mmol/L (85 mg/dL), they were 87%, 52%, 1.8, and 0.25, respectively. Glycated hemoglobin level had poorer test characteristics than fasting plasma glucose level or the OGCT. No studies compared the OGCT with International Association of the Diabetes and Pregnancy Study Groups (IADPSG) diagnostic criteria. LIMITATIONS: The lack of a gold standard for confirming GDM limits comparisons. Few data exist for screening tests before 24 weeks' gestation. CONCLUSION: The OGCT and fasting plasma glucose level (at a threshold of 4.7 mmol/L [85 mg/dL]) by 24 weeks' gestation are good at identifying women who do not have GDM. The OGCT is better at identifying women who have GDM. The OGCT has not been validated for the IADPSG diagnostic criteria.
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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 | 0.027 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".