Development of a core outcome set for diabetes after pregnancy prevention interventions (COS-DAP): a study protocol
Bibliographic record
Abstract
BACKGROUND: Gestational diabetes mellitus (GDM) increases the risk of adverse short- and long-term outcomes, including development of type 2 diabetes. The US Diabetes Prevention Program demonstrates this risk can be halved with an intensive health behavior change intervention in women with pre-diabetes averaging 12 years since a GDM pregnancy. In recent years, the number of studies looking at changing the behaviors of women with previous GDM closer to the time of delivery has steadily grown, but reported outcomes vary and most studies are not long enough or large enough to examine incident diabetes. This initiative aims to develop a core outcome set (COS) for interventions seeking to prevent diabetes after pregnancy (DAP) in both women with prior GDM and their families. METHODS: The COS-DAP project will use established COS methodology, in four stages: (1) a systematic literature review of DAP prevention intervention studies following GDM; (2) discussion and cataloguing of outcomes measured and implementation components at an investigator meeting; (3) a two-round online Delphi survey aimed at prioritizing the identified outcomes; and (4) a consensus meeting with key stakeholders to review, discuss, and refine suitable COS measures, using nominal group technique. DISCUSSION: COS-DAP aims to develop a COS for health behavior change interventions to prevent DAP. The COS is expected to enhance opportunities for comparison of future studies and allow for better synthesis of the effects. The inclusion of multiple stakeholder perspectives will increase the final COSs applicability and relevance. TRIAL REGISTRATION: Comet Initiative, COMET 1083; PROSPERO, CRD42018084853 . Registered in prospero on 03/01/2018.
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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 | 0.012 | 0.004 |
| 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 | 0.000 |
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".