Risk of in-hospital mortality following emergency department admission: Results from the geriatric EDEN cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine whether being admitted to emergency department (ED) for social disorders may predict a higher risk of in-hospital mortality among older inpatients. DESIGN: Prospective cohort study (mean follow-up: 9.1±10.0 days). SETTING: Angers University Hospital, France. PARTICIPANTS: Four hundred twenty-two inpatients (mean age 84.9±5.6years, 64.2% women). METHODS: At their admission to ED, inpatients aged 75 years and over received an assessment composed of 6 items: age, gender, number of drugs daily taken, history of falls during the past 6 months, usual place of life, and use of formal and/or informal home and social services. The reasons for admission to ED as well the diagnosis at the time of hospital discharge were separated into social and health disorders. The length of hospital stay was calculated in number of days using the hospital registry. Inpatients were separated into 2 groups based on the occurrence or not of death during the hospital stay. RESULTS: Older inpatients who died at hospital were more frequently institutionalized (P=0.034) and admitted to ED for social disorders (P=0.002) than those who did not. Multiple Cox regression model revealed that living in institution and social disorders as a reason for admission to ED were significantly associated with the occurrence of death at hospital (P=0.008 and P=0.036). Kaplan-Meier distributions of in-hospital mortality showed that home-living inpatients admitted to ED for social disorders died more and faster during hospitalization than those admitted for health disorders (P=0.016). CONCLUSION: Being admitted to ED for social disorders and living in institution predicted a higher risk of in-hospital mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".