The risk of death within 5 years of first hospital admission in older adults
Bibliographic record
Abstract
BACKGROUND: The risk of death in people after their first admission to hospital or first presentation to the emergency department for any reason is not known. The objective of this study was to estimate the risk of death among older adults who had had no admissions to hospital or emergency department visits in the preceding 5 years. METHODS: We used administrative data from Ontario, Canada, from 2007 to 2017 to measure the 5-year risk of death in community-dwelling adults aged 66 years and older after their first planned or unplanned hospital admission or emergency department visit, and among those who were neither admitted to hospital nor presented to the emergency department. We describe how this risk varied by age. RESULTS: Among 922 074 community-dwelling older adults, 12.7% died (116 940 deaths) over a follow-up of 3 112 528 person-years (standardized mortality rate 53.8 per 1000 person-years). After the first unplanned hospital admission, 39.7% died (59 234 deaths, standardized mortality rate 127.6 per 1000 person-years). After the first planned hospital admission, 13.0% died (10 775 deaths, standardized mortality rate 44.6 per 1000 person-years). After the first visit to the emergency department, 10.9% died (35 663 deaths, standardized mortality rate 36.2 per 1000 person-years). Among those with neither an emergency department visit nor hospital admission during follow-up, 3.1% died (11 268 deaths, standardized mortality rate 29.6 per 1000 person-years). Slightly more than half of all deaths were in those with first unplanned hospital admission (50.7%). INTERPRETATION: Death within 5 years of first unplanned hospital admission for older adults is frequent and common. Knowledge of this risk may influence counselling and patient preferences and may be useful in research and analyses for health system planning.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".