A Review of the Roles and Implementation of Pediatric Emergency Triage Systems in China and Other Countries
Bibliographic record
Abstract
A growing number of pediatric Emergency Department (ED) patients has become increasingly common in recent years, but only a small number of them are in true emergencies. It is particularly important to use pediatric triage systems to quickly assess the patients' conditions and determine the patients' priority in emergency treatment, ensuring timely treatment to critically ill patients and efficient utilization of medical resources. The Canadian Triage and Acuity Scale Paediatric Guidelines (PaedCTAS), Australasian Triage Scale (ATS), Emergency Severity Index (ESI), and Manchester Triage System (MTS) are internationally recognized pediatric triage systems. Some countries, such as China, Thailand, Singapore, Norway, South Africa, and South Korea, have created their own pediatric emergency triage systems in line with the situation of their respective countries. Pediatric Assessment Triangle (PAT) and Pediatric Early Warning Signs (PEWS) are usually used with triage systems for quick initial assessment of pediatric ED patients. The pediatric emergency triage systems developed in different countries have good reliability and are suitable for pediatric emergency triage. Because different triage systems had different performances, it is advisable to research the factors influencing the performance of pediatric triage systems. This was a narrative review. This article aims to review the roles and implementation of pediatric emergency triage systems in China and other countries.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".