Frailty Is Associated With Decreased Time Spent at Home After Critical Illness: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Frailty is characterized by vulnerability to stressors due to an accumulation of multiple functional deficits. Frailty is increasingly recognized as a risk factor for accelerated functional decline, increasing dependency, and risk of mortality. The objective of this study was to examine the association of frailty, at the time of critical care admission, with days alive at home and health care costs post-discharge. METHODS: This retrospective cohort study used linked administrative data (2010-2016) in Ontario, Canada. We identified all patients admitted at the intensive care unit (ICU), aged 19 years and above, assessed using the Resident Assessment Instrument for Home Care (RAI-HC), within 6 months prior to index hospitalization including an ICU stay. Patients were stratified as robust, pre-frail, or frail based on a validated Frailty Index. The primary outcome was days alive at home in the year after admission. Secondary outcomes included mortality, health care-associated costs, ICU interventions, long-term care admissions, and hospital readmissions. RESULTS: < .001). Mortality was higher among frail patients at 1 year (59.6% in the frail cohort vs 45.9% in robust patients; odds ratio for death 1.59 [1.49-1.69]). Frail patients also had higher rates of long-term care admission within 1 year (30.1% vs 10.6% in robust patients). Total health care-associated costs per person alive were $30 450 higher the year after admission in the frail cohort. CONCLUSIONS: Frailty prior to ICU admission among patients who were eligible for RAI-HC assessment was associated with higher mortality and fewer days spent at home following admission. Frail patients had markedly higher rates of long-term care admission and increased costs per life saved following critical illness. These findings add to the discussion of risk-benefit trade-offs for ICU admission.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".