Reliability of Canadian Emergency Department Triage and Acuity Scale (CTAS) in Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: The Canadian Emergency Department Triage and Acuity Scale (CTAS) is an integral part of the Canadian emergency medicine triaging system. There is growing interest and implementation of CTAS worldwide. However, little is known about its reliability outside Canada. The aim of this study was to determine the reliability agreement of CTAS in a tertiary care emergency center in Saudi Arabia. METHODS: Ten triage nurses (five senior and five junior nurses) utilized CTAS guidelines to independently assign a triage level for 160 real case-based scenarios. Quadratic weighted kappa statistics were used to measure raters' agreements. RESULTS: Raters provided 1600 triage category assignments to case scenarios for analysis. Intra-rater agreement was similar for both senior and junior nurses; for senior nurses (SN1) kappa 0.871 95 % CI (0.840-0.897), and for junior nurses (SN2) kappa 0.871 95 % CI (0.839-0.898). Inter-rater agreement for the SN1 versus SN2 nurses had statistically meaningful agreement across different triage levels (weighted kappa = 0.770) 95 % CI (0.742-0.797). CONCLUSIONS: CTAS has good reliability among emergency department (ED) triage nurses in King Abdulaziz Medical City (KAMC), Saudi Arabia. The findings suggest that CTAS might be a reliable instrument when applied in countries outside Canada.
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 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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".