Core outcome set for studies on pregnant women with vasa previa (COVasP): a study protocol
Bibliographic record
Abstract
INTRODUCTION: Vasa previa is a condition where fetal blood vessels run unprotected in the membranes, outside the umbilical cord, and cross the internal opening of the cervix. During rupture of membranes, these vessels can rupture and put the baby at serious risk of severe blood loss and death. Numerous studies are being conducted to improve diagnostic modalities and establish clear management plans to improve pregnancy outcomes. However, the lack of a standardised set of outcomes for studies on vasa previa makes it difficult to compare study findings and draw meaningful conclusions. Through this project, we will be developing a core outcome set for studies on pregnant women with vasa previa (COVasP). METHODS AND ANALYSIS: The development of COVasP will involve five steps. The first will be a systematic review, in which we will generate a long list of outcomes based on published studies in pregnancies complicated with vasa previa. The second will involve in-depth interviews with current and former patients, their family members and healthcare providers who care for these patients. This will be followed by a two-round Delphi survey, which will aim to narrow down the long list of outcomes into those considered important by four groups of 'stakeholders': (1) patients, family members and patient advocates/representatives, (2) healthcare providers, (3) researchers, epidemiologists and methodologists and (4) other stakeholders directly or indirectly involved in the management of these pregnancies such as administrators, guideline developers and policymakers. The fourth step will involve a face-to-face consensus meeting using a nominal group approach to establish a finalised core outcome set. The final step will involve measuring and defining the identified outcomes using a combination of systematic reviews and Delphi surveys. ETHICS AND DISSEMINATION: This study as well as consent forms for stakeholder participation have received approval from the Mount Sinai Hospital Research Ethics Board (REB number 18-0173-E) on 05 September 2018 and the Human Research Ethics Committee at The University of Technology Sydney, Australia on 30 July 2019 (UTS HREC reference number ETH19-3718). All progress will be documented on the international prospective register of systematic reviews and Core Outcome Measures in Effectiveness Trials databases. REGISTRATION DETAILS: http://www.comet-initiative.org/studies/details/1117.
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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 | 0.158 | 0.172 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".