TRIAGE SYSTEMS IN EMERGENCY CARE (REVIEW)
Bibliographic record
Abstract
The initial assessment of the condition of the patients, who need emergency medical care, is of crucial importance for their subsequent treatment. It is related to establishing the maximum time within which the patient must be examined by a physician, as well as the measures (manipulations, procedures, surgeries etc.) which must be undertaken for his/her appropriate and successful treatment. Since the units for emergency care are determined as high-risk ones, the use of a standardized system for performing an initial evaluation (the so-called triage) with the aim of ensuring timely and efficient medical care for emergency patients is necessary.The present article presents the existing international triage systems which are used in emergency care - the Australian – New Zealand system (ATS „Australasian triage scale“), the English (MTS – „Manchester-Triage-System“), the Canadian (CTAS - „Canadian triage and acuity scale“) and the American (ESI „emergency severity index“) ones.The main goal of all triage systems is primarily to decrease hospital mortality. In addition, the decrease to the minimum of the patients’ waiting time, hospitalization time, and the proper distribution of the medical staff are of crucial importance.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".