Prognostic Association Between Frailty and Post-Arrest Health Outcomes in Patients Receiving Home Care: A Population-Based Retrospective Cohort Study
Bibliographic record
Abstract
AIM: To evaluate the association between frailty and post-cardiac arrest survival, functional decline, and cognitive decline, among patients receiving home care. METHODS: Frailty was measured using the Clinical Frailty Scale (CFS) and a valid frailty index. We used multivariable logistic regression to measure the association between frailty and post-arrest outcomes after adjusting for age, sex, and arrest setting. Functional independence and cognitive performance were measured using the interRAI ADL Long-Form and Cognitive Performance Scale, respectively. We conducted sub-group analytics of in-hospital and out-of-hospital arrests. RESULTS: Our cohort consisted of 7,901 home care clients; most patients arrested out-of-hospital (55.4%) and were 75 years or older (66.3%). Most were classified as frail (94.2%) with a CFS score of 5 or greater. The 30-day survival rate was higher for in-hospital (26.6%) than out-of-hospital cardiac arrests (5.2%). Most patients who survived to discharge had declines in post-arrest functional independence (65.8%) and cognitive performance (46.5%). A one-point increase in the CFS decreased the odds of 30-day survival by 8% (aOR = 0.92; 95%CI = 0.87-0.97). A 0.1 unit increase in the frailty index reduced the odds of 30-day survival by 9% (aOR = 0.91; 95%CI = 0.86-0.96). The frailty index was associated with declines in functional independence (OR = 1.16; 95%CI = 1.02-1.31) and cognitive performance (OR = 1.24; 95%CI = 1.09-1.42), while the CFS was not. CONCLUSION: Frailty is associated with cardiac arrest survival and post-arrest cognitive and functional status in patients receiving home care. Post-cardiac arrest cognitive and functional status are best predicted using more comprehensive frailty indices.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".