Prognostic Value of Frailty for Older Patients with Heart Failure: A Systematic Review and Meta-Analysis of Prospective Studies
Bibliographic record
Abstract
OBJECTIVE: Numerous studies have investigated the prognostic role of frailty in elderly patients with heart failure (HF), but the limited size of the reported studies has resulted in continued uncertainty regarding its prognostic impact. The aim of this study was to integrate the findings of all available studies and estimate the impact of frailty on the prognosis of HF by performing a systematic review and meta-analysis. METHODS: 2017 to identify eligible prospective studies. The Newcastle-Ottawa Scale (NOS) was used to evaluate study quality. The association between frailty and HF outcomes was reviewed. Overall hazard ratios (HRs) for the effects of frailty on all-cause mortality were pooled using a fixed-effect model and publication bias was evaluated using funnel plots. RESULTS: A total of 10 studies involving 3033 elderly patients with HF were included in the systematic review and meta-analysis. All eligible studies indicated that frailty was of prognostic significance for HF patients. The HRs for the effects of frailty on all-cause mortality were 1.70 (95% confidence interval (CI): 1.41-2.04), based on the pooling of six studies that provided related data. However, publication bias was observed among the studies. CONCLUSIONS: Frailty has a high prevalence among older patients with HF. Elderly HF patients with frailty have a poorer prognosis than those without frailty. Further studies are now required to implement the use of frailty assessment tools and explore effective interventions for frailty in older HF patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".