PAEDIATRIC RESEARCH IN EMERGENCY DEPARTMENTS INTERNATIONAL COLLABORATIVE (PREDICT)
Bibliographic record
Abstract
15 May 2005 Dear Editor, Paediatric emergency medicine has made great strides since the inception of the subspecialty. However, many practices and guidelines in paediatric emergency medicine are still not sufficiently evidence based, practices of common paediatric conditions vary and compliance with evidence-based guidelines can be poor.1–5 Paediatric emergency research is hampered by a number of factors:6 serious outcomes and adverse events are rare; data collected at tertiary institutions are not necessarily generalizable to other settings; informed consent is difficult to obtain; data quality in the emergency setting can be poor; and funding for research is limited. Emergency care for children and adolescents can be improved and many of these obstacles can be overcome through rigorous multicentre research as shown in overseas paediatric emergency research networks, such as Pediatric Emergency Research Canada (PERC)7 and the Pediatric Emergency Care Applied Research Network (PECARN) in the USA.6 Given the lack of research infrastructure for multicentre emergency care research in Australia and New Zealand representatives from all seven Australian tertiary children's hospital emergency departments (ED), one general adult/paediatric ED in Australia and one tertiary children's hospital ED in New Zealand formed a research network, the Paediatric Research in Emergency Departments International Collaborative (PREDICT). The vision of PREDICT is to improve emergency care for children and adolescents through rigorous multicentre research. The goals are to improve the power of paediatric research activities by combining the efforts of individual institutions, to coordinate research activities, to create a research infrastructure and to mentor new investigators. Any physician, nurse, paramedic or researcher in Australia and New Zealand involved in the delivery or research of emergency care for children and adolescents can become a member of PREDICT. The structure and the decision-making process within PREDICT is centred on representatives of the participating institutions. The first two PREDICT projects have been initiated. The Basic Epidemiology Project will assess the epidemiology of the patients seen across the network. The initial disease-specific research project selected will assess differences in the management of status epilepticus across PREDICT sites. A recent study at an Australian tertiary paediatric ED has found that a minority of children arriving in status epilepticus at their institution responded to standard first- and second-line anticonvulsive therapy. 8 The PREDICT will develop a research agenda and roadmap to set priorities and to guide the in-depth evaluation of particular research areas. We aim for PREDICT to include more non-children's hospital EDs to ensure the applicability of research findings in a broad range of settings. Clinicians and institutions interested in participating in the PREDICT network or seeking more information are encouraged to contact one of the authors. We acknowledge the financial support of Murdoch Children's Research Institute, Parkville, Victoria, which provides ongoing funding for network infrastructure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".