EP16.20: Consensus protocol for diagnosis and management of singleton pregnancies with vasa previa: interim findings from a Delphi study
Bibliographic record
Abstract
In this study, we have aimed to establish consensus on the diagnosis and management of vasa previa using Delphi methodology. We conducted four rounds of focus group discussions (FGD) using a semi-structured questionnaire, with experts in the field of vasa previa and thematically analysed the data to generate statements for the first round of Delphi under four domains – definition, screening, management and timing of delivery. Experts were identified based on their publications on the subject of vasa previa. In the first round, participants rated each statement on a Likert scale, and consensus was defined as a median score of five. Thematic analysis of the FGDs generated 59 unique statements. In the first round, 57 experts (83.8% response rate) provided complete responses and consensus was reached on 12 statements. In the “definition” domain, the expert panel agreed that vasa previa can be diagnosed at any gestational age but should be confirmed later in pregnancy. For “screening,” the panel agreed on universal screening at the time of the routine anatomy scan. For admission criteria, the panel agreed on admitting patients with variable decelerations on the outpatient cardiotocogram, bleeding or rupture of membranes, and special social circumstances, including the patient's willingness to be admitted, anxiety, and difficult access to the medical centre. For “management”, consensus was reached on not routinely recommending fetoscopic laser ablation and performing this only as an experimental therapy. Experts also recommended against bed rest. 91.2% of experts recommended delivering between 35 and 36 weeks and agreed against routine delivery before 34 or after 38 weeks. In the first round of our Delphi study, the international expert panel established a consensus on the universal screening of vasa previa at the time of the routine anatomy scan. The subsequent round of our study is underway and will provide further insight.
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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 | 0.241 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 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; 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".