The reliability of the Canadian triage and acuity scale: Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although the Canadian Triage and Acuity Scale (CTAS) have been developed since two decades ago, the reliability of the CTAS has not been questioned comparing to moderating variable. AIMS: The study was to provide a meta-analytic review of the reliability of the CTAS in order to reveal to what extent the CTAS is reliable. MATERIALS AND METHODS: Electronic databases were searched to March 2014. Only studies were included that had reported samples size, reliability coefficients, adequate description of the CTAS reliability assessment. The guidelines for reporting reliability and agreement studies (GRRAS) were used. Two reviewers independently examined abstracts and extracted data. The effect size was obtained by the z-transformation of reliability coefficients. Data were pooled with random-effects models and meta-regression was done based on method of moments estimator. RESULTS: Fourteen studies were included. Pooled coefficient for the CTAS was substantial 0.672 (CI 95%: 0.599-0.735). Mistriage is less than 50%. Agreement upon the adult version, among nurse-physician and near countries is higher than pediatrics version, other raters and farther countries, respectively. CONCLUSION: The CTAS showed acceptable level of overall reliability in the emergency department but need more development to reach almost perfect agreement.
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 | 0.032 | 0.094 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.039 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".