Characteristics and outcomes of older patients in the emergency department
Bibliographic record
Abstract
Background: Less is known about patients classified as "less acute" during triage, although elderly patients in the emergency department (ED) are a high-risk population. Our study concentrated on the outcomes of patients 65 and older with low acuity triage evaluations. Methods: This health records study assessed emergency department (ED) patients and controls with a Canadian Triage Acuity Scale score of 4 or 5 and age 65 or older. The information collected covered patient demographics, ED management, disposition, and a subsequent visit or hospital admission after 14 days. Chi-square testing and descriptive analysis of the data were both performed. Results: A stratified analysis plan was performed on patients 65 to 74, 75 to 84, and 85 years or older. The elder cohort had an average age of 77.4 years (range 64 to 99), while the control group of adults aged 39 to 54 had a mean age of 46.2 years. Most patients (86.3% older, 93.8% control) were prioritised and sent to the ED's ambulatory care unit. 11.1% of patients in the older cohort were triaged and then sent to an isolated stretcher area. Emergency medical services brought an elderly patient who had fallen and was being transferred on a backboard to the acute monitored area of the department. The elder cohort's likelihood of hospital admission was considerably higher (p=0.017). Conclusion: The present study shows that even "low acuity" older individuals risk returning and being admitted within 14 days after visiting the 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".