The Impact of Frailty According to Clinical Frailty Scale on Clinical Outcome in Patients with Heart Failure
Bibliographic record
Abstract
AIMS: There is currently no gold standard in evaluating frailty in patients with heart failure (HF), and the prognostic value of frailty according to the Canadian Study of Health and Aging Clinical Frailty Scale (CFS) on mortality in patients with HF is still unknown. METHODS AND RESULTS: Among consecutive 596 patients after their discharge from HF in Kokura Memorial Hospital (Kitakyushu, Japan) during 2015, their frailty at discharge was assessed according to CFS. Patients were classified into three groups: low (N = 232, 38.9%), intermediate (N = 230, 38.6%), and high (N = 134, 22.5%). The primary endpoint was defined as 2 year all-cause death. The mean age was 76.6 ± 10.1 years, and 55.3% were men in entire cohort. There were significant differences in age, living environment, and dementia among low, intermediate, and high CFS groups. Left ventricular ejection fraction (LVEF) and co-morbidities such as severe renal failure and severe anaemia tended to increase with frailty severity, while body mass index (BMI) and albumin level tended to decrease with frailty severity. Two year cumulative incidences of all-cause death for the three groups were 12.8%, 25.4%, and 52.7% (P < 0.001), respectively. This significant difference in the risk for all-cause death among the CFS groups was driven by the risk for cardiac (8.6%, 14.2%, and 31.0%, respectively, P < 0.001) and non-cardiac death (4.6%, 13.0%, and 31.4%, respectively, P < 0.001). The multivariate analysis showed that high frailty was independently associated with all-cause death (intermediate CFS group: adjusted hazard ratio, 1.43, 95% confidence interval, 0.86-2.36, P = 0.16; high CFS group: adjusted hazard ratio, 3.90, 95% confidence interval, 2.32-6.55, P < 0.001), and this result was consistent, irrespective of stratification based on age, sex, BMI, and LVEF without significant interaction. CONCLUSIONS: The simple CFS tool was successful in predicting the risk for all-cause death in patients with HF, and frailty according to CFS was independently associated with all-cause death irrespective of stratification based on age, sex, BMI, and LVEF without significant interaction. The CFS is a valuable prognostic tool in clinical settings.
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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 | 0.001 |
| 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".