Who Doesn’t Come Home? Factors Influencing Mortality Among Long-Term Care Residents Transitioning to and From Emergency Departments in Two Canadian Cities
Bibliographic record
Abstract
Residents of long-term care (LTC) whose deaths are imminent are likely to trigger a transfer to the emergency department (ED), which may not be appropriate. Using data from an observational study, we employed structural equation modeling to examine relationships among organizational and resident variables and death during transitions between LTC and ED. We identified 524 residents involved in 637 transfers from 38 LTC facilities and 2 EDs. Our model fit the data, (χ 2 = 72.91, df = 56, p = .064), explaining 15% variance in resident death. Sustained shortness of breath (SOB), persistent decreased level of consciousness (LOC) and high triage acuity at ED presentation were direct and significant predictors of death. The estimated model can be used as a framework for future research. Standardized reporting of SOB and changes in LOC, scoring of resident acuity in LTC and timely palliative care consultation for families in the ED, when they are present, warrant further investigation.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".