Importance of effective collaboration between pediatric intensive care and emergency departments
Bibliographic record
Abstract
Pediatric critical care and pediatric emergency medicine are disciplines that share responsibility for providing care for acutely injured or critically ill children. In many parts of the developed world, these disciplines are recognized subspecialties of pediatrics with excellent training programs, a welldefined body of knowledge, sufficient practitioners at the senior level and a track record of clinical and academic productivity [1,2]. Indeed, from modest beginnings in the 1960s, pediatric critical care medicine has evolved and can boast dramatic major advances in the areas of lung injury, sepsis, traumatic brain injury and postoperative care. Pediatric emergency medicine has also made significant advances in the evaluation and treatment of respiratory distress, asthma, croup, epiglottitis, traumatic injuries, poisonings, cardiopulmonary resuscitation and sepsis. Both pediatric emergency medicine and pediatric critical care have developed impressive and aggressive research programs both in the USA and Canada [101–104]. What these disciplines share in common is their expertise to render care to patients with the greatest physiological instability. For many of these children, critical illness first occurs in diverse settings outside the hospital environment, and early recognition and early aggressive therapy can lead to improved outcomes. Furthermore, the best outcome can be guaranteed if there is good communication and a seamless continuum of care starting in the pre-hospital setting, which is linked to an efficient transport system and tertiary pediatric emergency and tertiary pediatric critical care teams (Figure 1).
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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 | 0.024 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".