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Record W4377939774 · doi:10.1111/apa.16858

Comparison between local and three validated triage systems in an emergency department for 2126 children under 3 months

2023· article· en· W4377939774 on OpenAlexaboutno aff
A. Mollet, Louis Rousselet, Domitille Tristram, Nicolas Kalach, M. Pelzer, Marie‐Laure Charkaluk, Mathilde Delebarre

Bibliographic record

VenueActa Paediatrica · 2023
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTriageMedicineEmergency departmentEmergency medicineProspective cohort studyMedical emergencyRetrospective cohort studyPediatricsSurgeryNursing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.345
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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