Impact of Adverse Events on Hospital Disposition in Community-Dwelling Seniors Admitted to Acute Care
Bibliographic record
Abstract
Older adults (> or =65 years) have been identified as a high-risk group for the occurrence of adverse events (AEs) in hospital. The purpose of this paper is to describe the association between AEs and disposition for a population of hospitalized seniors. All community-dwelling seniors admitted to an acute care in-patient unit were eligible for inclusion in this retrospective cohort study conducted at an adult tertiary care facility in Atlantic Canada between July 1, 2005, and March 31, 2006. AEs were identified from administrative data using validated screening criteria derived from the International Classification of Diseases (ICD) diagnosis and external cause of injury codes. Of the 982 eligible patients, 140 (14%) had evidence of at least one AE. There were 136 in-hospital deaths (14%). There was no significant difference in the proportion of deaths between those who experienced an AE and those who did not. However, of the 29 patients who were discharged to a long-term care facility, a significantly higher proportion had an in-hospital AE (6% versus 2%, p < .009). The potential contribution of an AE to the subsequent placement in a long-term care facility offers a compelling reason to develop prevention strategies for hospitalized seniors.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".