NIH consensus development conference: diagnosing gestational diabetes mellitus.
Bibliographic record
Abstract
OBJECTIVE: To provide healthcare providers, patients, and the general public with a responsible assessment of currently available data on diagnosing gestational diabetes mellitus (GDM). PARTICIPANTS: A non-U.S. Department of Health and Human Services, nonadvocate 15-member panel representing the fields of obstetrics and gynecology, maternal-fetal medicine, pediatrics, diabetic research, biostatistics, women's health issues, health services research, decision analysis, health management and policy, health economics, epidemiology, and community engagement. In addition, 16 experts from pertinent fields presented data to the panel and conference audience. EVIDENCE: Presentations by experts and a systematic review of the literature prepared by the University of Alberta Evidence-based Practice Centre, through the Agency for Healthcare Research and Quality (AHRQ). Scientific evidence was given precedence over anecdotal experience. CONFERENCE PROCESS: The panel drafted its statement based on scientific evidence presented in open forum and on published scientific literature. The draft statement was posted at http://prevention.nih.gov/ for public comment and the panel released a final statement approximately 10 weeks later. The final statement is an independent report of the panel and is not a policy statement of the NIH or the Federal Government. CONCLUSIONS: At present, GDM is commonly diagnosed in the United States using a 1-hour screening test with a 50-gram glucose load followed by a 3-hour 100-gram glucose tolerance test (a two-step approach) for those found to be abnormal on the screen. This approach identifies approximately 5% to 6% of the population as having GDM. In contrast, newly proposed diagnostic strategies rely on the administration of a 2-hour glucose tolerance test (a one-step approach) with a fasting component and a 75-gram glucose load. These strategies differ on whether a 1-hour sample is included, whether two abnormal values are required, and the diagnostic cutoffs that are used. The International Association of Diabetes and Pregnancy Study Groups (IADPSG) has proposed diagnostic thresholds based on demonstrated associations between glycemic levels and an increased risk of obstetric and perinatal morbidities. The panel considered whether a one-step approach to the diagnosis of GDM should be adopted in place of the two-step approach. The one-step approach offers certain operational advantages. The current two-step approach is used only during pregnancy and is largely restricted to the United States. There would be value in a consistent, international diagnostic standard across one's lifespan. This unification would allow better standardization of best practices in patient care and comparability of research outcomes. The one-step approach also holds potential advantages for women and their health care providers, as it would allow a diagnosis to be achieved within the context of one visit as opposed to two. However, the one-step approach, as proposed by the IADPSG, is anticipated to increase the frequency of the diagnosis of GDM by twofold to threefold, to a prevalence of approximately 15% to 20%. There are several concerns regarding the diagnosis of GDM in these additional women. It is not well understood whether the additional women identified by this approach will benefit from treatment, and if so, to what extent. Moreover, the care of these women will generate additional direct and indirect health care costs. There is also evidence that the labeling of these women may have unintended consequences, such as an increase in cesarean delivery and more intensive newborn assessments. In addition, increased patient costs, life disruptions, and psychosocial burdens have been identified. Available studies do not provide clear evidence that a one-step approach is cost-effective in comparison with the current two-step approach. After much deliberation, the panel believes that there are clear benefits to international standardization with regard to the one-step approach. Nevertheless, at present, the panel believes that there is not sufficient evidence to adopt a one-step approach. The panel is particularly concerned about the adoption of new criteria that would increase the prevalence of GDM, and the corresponding costs and interventions, without clear demonstration of improvements in the most clinically important health and patient-centered outcomes. Thus, the panel recommends that the two-step approach be continued. However, given the potential benefits of a one-step approach, resolution of the uncertainties associated with its use would warrant revision of this conclusion.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 0.006 |
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".