Impact of frailty on outcomes of elderly patients with atrial fibrillation: A systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Atrial fibrillation (AF) prevalences have risen globally due to the increasing aging populations posing significant health challenges. Frailty, a state characterized by weak physiological reserves, has emerged as a crucial factor influencing cardiovascular disease outcomes, including those in patients with AF. With this systematic review and meta-analysis, we aimed to elucidate the impact of frailty on mortality, and the incidences of stroke, major bleeding events, and other outcomes in elderly patients with AF. Method: A comprehensive search of PubMed, EMBASE, and Scopus databases yielded 1302 relevant records from inception until January 2024. We screened them to assess their eligibility for our study. We included data from 23 studies into our analysis, covering a diverse global population. We also assessed the quality of the included studies by assigning Newcastle- Ottawa Scale scores. Results: Frailty demonstrated a consistent association with increased all-cause mortality (Hazards ratio [HR] 2.46 in frail individuals). Frailty also correlated with elevated risks of stroke (HR, 1.46) and major bleeding events (HR, 1.34). Our analysis also revealed non-significant associations with cardiovascular death and intra-cranial hemorrhage. Conclusion: Frailty significantly increases the frequency of adverse outcomes in elderly patients with AF; thus, these patients should be managed with tailored risk stratification tools. Integrating frailty assessments into clinical decision-making should aid in optimizing care strategies and enhance outcomes in this vulnerable population. doi: https://doi.org/10.12669/pjms.41.3.11357 How to cite this: Yao J, Chen K, He Z, Chen D. Impact of frailty on outcomes of elderly patients with atrial fibrillation: A systematic review and meta-analysis. Pak J Med Sci. 2025;41(3):891-901. doi: https://doi.org/10.12669/pjms.41.3.11357 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".