Establishing the international research priorities for pediatric emergency medicine point‐of‐care ultrasound: A modified Delphi study
Bibliographic record
Abstract
BACKGROUND: The Pediatric Emergency Medicine (PEM) Point-of-care Ultrasound (POCUS) Network (P2Network) was established in 2014 to provide a platform for international collaboration among experts, including multicenter research. The objective of this study was to use expert consensus to identify and prioritize PEM POCUS topics, to inform future collaborative multicenter research. METHODS: Online surveys were administered in a two-stage, modified Delphi study. A steering committee of 16 PEM POCUS experts was identified within the P2Network, with representation from the United States, Canada, Italy, and Australia. We solicited the participation of international PEM POCUS experts through professional society mailing lists, research networks, social media, and "word of mouth." After each round, responses were refined by the steering committee before being reissued to participants to determine the ranking of all the research questions based on means and to identify the high-level consensus topics. The final stage was a modified Hanlon process of prioritization round (HPP), which emphasized relevance, impact, and feasibility. RESULTS: Fifty-four eligible participants (16.6%) provided 191 items to Survey 1 (Round 1). These were refined and consolidated into 52 research questions by the steering committee. These were issued for rating in Survey 2 (Round 2), which had 45 participants. At the completion of Round 2, all questions were ranked with six research questions reaching high-level consensus. Thirty-one research questions with mean ratings above neutral were selected for the HPP round. Highly ranked topics included clinical applications of POCUS to evaluate and manage children with shock, cardiac arrest, thoracoabdominal trauma, suspected cardiac failure, atraumatic limp, and intussusception. CONCLUSIONS: This consensus study has established a research agenda to inform future international multicenter PEM POCUS trials. This study has highlighted the ongoing need for high-quality evidence for PEM POCUS applications to guide clinical practice.
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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 | 0.197 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".