Association of admission frailty and frailty changes during cardiac rehabilitation with 5-year outcomes
Bibliographic record
Abstract
AIMS: Examine the association between (1) admission frailty and (2) frailty changes during cardiac rehabilitation (CR) with 5-year outcomes (i.e. time to mortality, first hospitalization, first emergency department (ED) visit, and number of hospitalizations, hospital days, and ED visits). METHODS AND RESULTS: Data from patients admitted to a 12-week CR programme in Halifax, Nova Scotia, from May 2005 to April 2015 (n = 3371) were analysed. A 25-item frailty index (FI) estimated frailty levels at CR admission and completion. FI improvements were determined by calculating the difference between admission and discharge FI. CR data were linked to administrative health data to examine 5-year outcomes [due to all causes and cardiovascular diseases (CVDs)]. Cox regression, Fine-Gray models, and negative binomial hurdle models were used to determine the association between FI and outcomes. On average, patients were 61.9 (SD: 10.7) years old and 74% were male. Mean admission FI scores were 0.34 (SD: 0.13), which improved by 0.07 (SD: 0.09) by CR completion. Admission FI was associated with time to mortality [HRs/IRRs per 0.01 FI increase: all causes = 1.02(95% CI 1.01,1.04); CVD = 1.03(1.02,1.05)], hospitalization [all causes = 1.02(1.01,1.02); CVD = 1.02(1.01,1.02)], ED visit [all causes = 1.01(1.00,1.01)], and the number of hospitalizations [all causes = 1.02(95% CI 1.01,1.03); CVD = 1.02(1.00,1.04)], hospital days [all causes = 1.01(1.01,1.03)], and ED visits [all causes = 1.02(1.02,1.03)]. FI improvements during CR had a protective effect regarding time to all-cause hospitalization [0.99(0.98,0.99)] but were not associated with other outcomes. CONCLUSION: Frailty status at CR admission was related to long-term adverse outcomes. Frailty improvements during CR were associated with delayed all-cause hospitalization, in which a larger effect was associated with a greater chance of improved outcome.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".