Impact of Frailty on Mortality and Hospitalization in Chronic Heart Failure: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background Although frailty has been associated with increased risks for hospitalization and mortality in chronic heart failure, the precise average effect remains uncertain. We performed a systematic review and meta‐analysis to summarize the hazards for mortality and incident hospitalization in patients with heart failure and frailty compared with those without frailty and explored the heterogeneity underlying the effect size estimates. Methods and Results MEDLINE , EMBASE, and Cochrane databases were queried for articles published between January 1966 and March 2018. Predefined selection criteria were used. Hazard ratios ( HRs ) were pooled for meta‐analyses, and where odds ratios were used previously, original data were recalculated for HR . Overlapping data were consolidated, and only unique data points were used. Study quality and bias were assessed. Eight studies were included for mortality (2645 patients), and 6 studies were included for incident hospitalization (2541 patients) during a median follow‐up of 1.82 and 1.12 years, respectively. Frailty was significantly associated with an increased hazard for mortality ( HR , 1.54; 95% confidence interval, 1.34–1.75; P <0.001) and incident hospitalization ( HR , 1.56; 95% confidence interval, 1.36–1.78; P <0.001) in chronic heart failure. The Fried phenotype estimated a 16.9% larger effect size than the combined Fried/non‐Fried frailty assessment for the end point of mortality ( HR , 1.80; 95% confidence interval, 1.41–2.28; P <0.001), but not for hospitalization ( HR , 1.57; 95% confidence interval, 1.30–1.89; P <0.001). Study heterogeneity was found to be low (I 2 =0%), and high quality of studies was verified by the Newcastle‐Ottawa scale. Conclusions Overall, the presence of frailty in chronic heart failure is associated with an increased hazard for death and hospitalization by ≈1.5‐fold.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".