Benefits and Harms of Treating Gestational Diabetes Mellitus: A Systematic Review and Meta-analysis for the U.S. Preventive Services Task Force and the National Institutes of Health Office of Medical Applications of Research
Bibliographic record
Abstract
BACKGROUND: Outcomes of treating gestational diabetes mellitus (GDM) are not well-established. PURPOSE: To summarize evidence about the maternal and neonatal benefits and harms of treating GDM. DATA SOURCES: 15 electronic databases from 1995 to May 2012, gray literature, Web sites of relevant organizations, trial registries, and reference lists. STUDY SELECTION: English-language randomized, controlled trials (n = 5) and cohort studies (n = 6) of women without known preexisting diabetes. DATA EXTRACTION: One reviewer extracted data, and a second reviewer verified them. Two reviewers independently assessed methodological quality and evaluated strength of evidence for primary outcomes by using a Grading of Recommendations Assessment, Development and Evaluation approach. DATA SYNTHESIS: All studies compared diet modification, glucose monitoring, and insulin as needed with no treatment. Women who were treated had more prenatal visits than those in control groups. Moderate evidence showed fewer cases of preeclampsia, shoulder dystocia, and macrosomia in the treated group. Evidence was insufficient for maternal weight gain and birth injury. Low evidence showed no difference between groups for neonatal hypoglycemia. Evidence was insufficient for long-term metabolic outcomes among offspring. No difference was found for cesarean delivery (low evidence), induction of labor (insufficient evidence), small-for-gestational-age neonates (moderate evidence), or admission to a neonatal intensive care unit (low evidence). LIMITATIONS: Evidence is low or insufficient for many outcomes of greatest clinical importance. The strongest evidence supports reductions in intermediate outcomes; however, other factors (for example, maternal weight and gestational weight gain) may impart greater risk than GDM, particularly when glucose levels are modestly elevated. CONCLUSION: Treating GDM results in less preeclampsia, shoulder dystocia, and macrosomia; however, current evidence does not show an effect on neonatal hypoglycemia or future poor metabolic outcomes. There is little evidence of short-term harm of treating GDM other than an increased demand for services.
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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 | 0.047 | 0.118 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.026 | 0.050 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".