Bibliographic record
Abstract
Purpose: Emergency department (ED) overcrowding is a common occurrence, and requires performance of appropriate triage to determine the priority for patient treatments. Undertriage, defined as inappropriate assignment of a low level of severity during triage, delays the initiation of treatment and may lead to deterioration of severely ill or injured patients. The aim of this observational study was to evaluate the clinical characteristics of undertriage patients and their risk exposure to a worsening prognosis. Methods: Subjects were ED patients admitted to a university affiliated hospital from Jan 1, 2010 to Dec 31, 2010, and they were triaged according to the modified Canadian Triage and Acuity Scale. Patients who were initially categorized as non-emergency cases (scale 4 or 5) but later recategorized as emergency cases (scale 1 or 2) were defined as the undertriage group. Triage patients who did not receive a change of severity categorization were assigned to a low-acuity group for non-emergency cases, and a high-acuity group for emergency cases. The clinical characteristics and worsening prognosis of the undertriage group were compared with low- and high-acuity groups. Worsening prognosis included cardiac arrest and the admission to the intensive care unit. Results: Patients in the undertriage group were 0.9% of the total study participants. The undertriage group predominantly included elderly males with head and neck injuries, or hemato-oncology diseases. Worsening prognosis was less likely in the undertriage group than in the high-acuity group, and more likely than in the low-acuity group. Conclusion: Undertriage was not common. However, worsening prognosis was very high in the undertriage group as compared to the low-acuity group. Prudential concern is required to avoid undertriage with the elderly, and patients with head and neck injuries, or hemato-oncology diseases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".