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Record W2751488002 · doi:10.3346/jkms.2017.32.10.1702

Clinical Considerations When Applying Vital Signs in Pediatric Korean Triage and Acuity Scale

2017· article· en· W2751488002 on OpenAlexaboutno aff
Bongjin Lee, Do Kyun Kim, June Dong Park, Young Ho Kwak

Bibliographic record

VenueJournal of Korean Medical Science · 2017
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersSeoul National University HospitalSeoul National University
KeywordsVital signsTriageScale (ratio)MedicineMedical emergencyIntensive care medicineEmergency medicineSurgeryGeographyCartography

Abstract

fetched live from OpenAlex

Initial vital signs of children at the emergency department may be abnormal because of anxiety and irritability, resulting in unrealistic triage levels. This study aimed to evaluate the effectiveness of pediatric triage by clinical decision based on the patient's general condition. The Pediatric Korean Triage and Acuity Scale (PedKTAS) has been used nationwide for triage since 2016. The triage level, as assessed by an experienced triage nurse and based on the patient's clinical condition, was defined as the 'real practice (RP)-level,' while the re-calculated triage level, as assessed by the direct application of initial vital signs, was defined as the 'simulation (S)-level.' A total of 22,841 patients were triaged during the study period. The hospitalization rate according to RP-PedKTAS levels exhibited a significant correlation with the expected hospitalization rate suggested by the Pediatric Canadian Triage and Acuity Scale (CTAS) (P = 0.002), whereas the S-PedKTAS levels did not (P = 0.151). Compared with the previously reported pediatric CTAS level-specific hospitalization rate and intensive care unit (ICU) admission rate, RP-PedKTAS was significantly correlated with both hospitalization rate and ICU admission rate (P = 0.001 and P = 0.012, respectively). However, S-PedKTAS showed no significant correlation in both (P = 0.267 and P = 0.188, respectively). The determination of triage levels based on clinical decision rather than the direct application of abnormal initial vital signs to PedKTAS is more accurate in predicting the hospitalization rate and ICU admission rate.

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)0.006
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.398
Teacher spread0.333 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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