[Emergency room deaths: 3-month retrospective analysis].
Bibliographic record
Abstract
OBJECTIVES: Determine the characteristics of patients who died in the emergency unit and assess the number for whom care was limited or withdrawn. METHODS: A 3-month single-center retrospective study of all the patients who died in the emergency room. Bivariate analysis was used to compare the clinical characteristics of patients who died despite maximum care (MC) with those for whom care was limited (LC). RESULTS: 84 patients died during the study period: 48 men and 36 women (mean age: 73 +/- 18 years). Half had normal mobility (43 patients, 50%), and 35 (40%) lived at home. Nearly all (72 patients, 72%) had a severe chronic disease. In descending order, death was ascribed to neurological (n = 22, 24%), cardiac (n = 14, 15%), septic (n = 13, 14%) and respiratory (n = 9, 10%) causes. The decision was made to limit or stop active care for 73 patients (84%) and recorded in 48 case files (55%). The principal differences between patients receiving MC and LC were respectively C and D Knaus classification and their age. CONCLUSION: Death is frequent in emergency units and often strikes elderly patients with impaired mobility and severe chronic diseases. The decisions to limit or stop active care are the predominant direct cause, but their modalities warrant further exploration in a prospective study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".