Comparison between local and three validated triage systems in an emergency department for 2126 children under 3 months
Bibliographic record
Abstract
AIM: Triage of patients less than 3 months old was not already studied. The aim was to evaluate Paediatric Emergency Department triage in patients less than 3 months old and newborns using a local system in comparison with three validated paediatric triage systems (Canadian Triage and Acuity Scale, Manchester Triage System and Emergency Severity Index) and to determine inter-system agreement. METHODS: All admissions of patients less than 3 months old admitted to the Emergency Department of the Saint Vincent University Hospital between April 2018 and December 2019 were included. The local triage system level was determined prospectively for comparison with retrospectively calculated triage levels of the validated systems. Hospitalisation rates were compared and inter-system agreements determined. RESULTS: Among emergency admissions, 2126 were included (55% males, mean age 45 days). Hospitalisation rate increased with priority severity as determined by all triage systems studied. Cohen's kappa showed slight agreement between the local triage system and the Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System (weighted kappa = 0.133, 0.185 and 0.157 respectively). CONCLUSION: Whether prospective or retrospective triage used, the systems studied exhibited good association with hospitalisation rate for patients aged less than 3 months and newborn infants.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".