Development of a Core Outcome Set for research on critically ill obstetric patients: A study protocol
Bibliographic record
Abstract
Background Current data on critical illness during pregnancy are insufficient for evidence-based decision making. Core outcome sets are promoted to improve reporting of outcomes important to decision makers. We aim to develop a Core Outcome Set for research on critically ill obstetric patients (COSCO study). Methods We will perform a systematic review of studies on critical illness in pregnancy and focus groups or interviews with women who were critically ill while being pregnant. These data will inform an international Delphi survey where stakeholders will rank proposed outcomes. Selected outcomes will be brought forward to a consensus meeting where core outcomes will be defined. We will then complete a second consensus process to define measures for each core outcome. Conclusion The Core Outcome Set on Critically ill Obstetric patients study aims to develop a set of core outcomes to be part of all studies on critically ill obstetric patients. Implementation of this core outcome set will help improve future research efforts. Trial registration: This study is registered on the COMET-initiative website (COS #916). This systematic review is registered on PROSPERO (CRD #42017071944).
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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 | 0.193 | 0.171 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.048 | 0.010 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".