Pediatric Emergency Care Research Networks: A Research Agenda
Bibliographic record
Abstract
BACKGROUND: Pediatric emergency care research networks have evolved substantially over the past two decades. Some networks are specialized in specific areas (e.g., sedation, simulation) while others study a variety of medical and traumatic conditions. Given the increased collaboration between pediatric emergency research networks, the logical next step is the development of a research priorities agenda to guide global research in emergency medical services for children (EMSC). OBJECTIVES: An international group of pediatric emergency network research leaders was assembled to develop a list of research priorities for future collaborative endeavors within and between pediatric emergency research networks. METHODS: Before an in-person meeting, we used a modified Delphi approach to achieve consensus around pediatric emergency research network topic priorities. Further discussions took place on May 15, 2018, in Indianapolis, Indiana, at the Academic Emergency Medicine (AEM) consensus conference "Aligning the Pediatric Emergency Medicine Research Agenda to Reduce Health Outcome Gaps." Here, a group of 40 organizers and participants met in a 90-minute "breakout" session to review and further develop the initial priorities. RESULTS: We reached consensus on five clinical research priorities that would benefit from collaboration among the existing and future emergency networks focused on EMSC: sepsis, trauma, respiratory conditions, pharmacology of emergency conditions, and mental health emergencies. Furthermore, we identified nonclinical research priorities categorized under the domains of technology, knowledge translation, and organization/administration of pediatric emergency care. CONCLUSION: The identification of pediatric emergency care network research priorities within the domains of clinical care, technology, knowledge translation and organization/administration of EMSC will facilitate and help focus collaborative research within and among research networks globally. Engagement of essential stakeholders including EMSC researchers, policy makers, patients, and their caregivers will stimulate advances in the delivery of emergency care to children around the globe.
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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 | 0.219 | 0.162 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.034 | 0.054 |
| Open science | 0.007 | 0.024 |
| Research integrity | 0.029 | 0.028 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".