Validity of the Pediatric Canadian Triage Acuity Scale in a tertiary children’s hospital in Israel
Bibliographic record
Abstract
OBJECTIVE: In 2015, the Israeli Ministry of Health issued national guidelines demanding the use of a five-level triage system in pediatric emergency departments (EDs). The present study aimed to evaluate the validity of the Pediatric Canadian Triage Acuity Scale (PedCTAS) in the ED of a tertiary children's hospital in Israel. METHODS: A retrospective cohort study of all patients admitted between January 2011 and December 2015 was carried out. The proportion of hospitalization was the primary outcome measure. The secondary outcomes were proportion of admissions to the ICU, proportions of patients who left without being seen (LWBS), and length of stay (LOS) in the ED. RESULTS: A total of 83 609 patients were included in our analysis. Triage levels 1-5 included 533 (0.6%), 4428 (5.3%), 46 461 (55.6%), 28 510 (34.1%), and 3677 (4.4%) patients, respectively. Hospitalization proportions were 70, 51, 28, 15, and 12% for triage levels 1, 2, 3, 4, and 5, respectively. Admission proportions to ICU were 24.2, 3.05, 0.24, 0.05, and 0.05% for PedCTAS levels 1, 2, 3, 4, and 5, respectively. The proportions of LWBS were 0.001, 0.002, and 0.005% for triage levels 3, 4, and 5, respectively. LOS was shorter as the triage level increased from 2 to 5. CONCLUSION: Triage level was predictive of hospitalization, admission to the ICU, and proportions of LWBS and LOS in the ED. The findings suggest validity of the PedCTAS in this cohort. This is the first report of the performance of a triage tool in an Israeli ED.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".