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Validation of different pediatric triage systems in the emergency department

2017· article· en· W2733028049 on OpenAlexaboutno aff
Kanokwan Aeimchanbanjong, Uthen Pandee

Bibliographic record

VenueWorld Journal of Emergency Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersMahidol University
KeywordsTriageMedicineEmergency departmentPsychosocialReliability (semiconductor)Observational studyMedical emergencyKappaEmergency medicinePediatricsPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Triage system in children seems to be more challenging compared to adults because of their different response to physiological and psychosocial stressors. This study aimed to determine the best triage system in the pediatric emergency department. METHODS: This was a prospective observational study. This study was divided into two phases. The first phase determined the inter-rater reliability of five triage systems: Manchester Triage System (MTS), Emergency Severity Index (ESI) version 4, Pediatric Canadian Triage and Acuity Scale (CTAS), Australasian Triage Scale (ATS), and Ramathibodi Triage System (RTS) by triage nurses and pediatric residents. In the second phase, to analyze the validity of each triage system, patients were categorized as two groups, i.e., high acuity patients (triage level 1, 2) and low acuity patients (triage level 3, 4, and 5). Then we compared the triage acuity with actual admission. RESULTS: 0.74-0.81). CONCLUSION: RTS illustrated almost perfect inter-rater reliability. Meanwhile, ESI and CTAS illustrated good inter-rater reliability. Finally, ESI illustrated the appropriate validity for triage system.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.361
Teacher spread0.299 · 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.

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

Citations42
Published2017
Admission routes1
Has abstractyes

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