Cognitive outcomes post-catheter ablation for atrial fibrillation: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background Atrial fibrillation (AF) is a known risk factor for cognitive impairment and dementia. Recent data suggests that successful restoration of sinus rhythm by catheter ablation improves cognitive outcomes. Purpose: Our aim was to perform a systematic review and meta-analysis of the available data regarding the effectiveness of AF catheter ablation on neurocognitive outcomes. Methods: A comprehensive literature search was performed through December 1, 2020, for all eligible studies comparing neurocognitive outcomes in AF patients with or without AF catheter ablation. Clinical outcomes included rate of dementia, cognitive function by Montreal Cognitive Assessment (MOCA) and Mini-Mental State Examination (MMSE) scores. Additional outcomes included the impact of time in sinus rhythm on neurocognitive outcomes. Results: We identified 11 studies which evaluated the effect of AF catheter ablation on dementia rate, MMSE and MOCA score. Meta-analysis of observational results indicates a decreased risk of dementia (risk ratio 0.51; 95% CI: 0.43 to 0.60; p <0.001) and an improvement in MOCA scores (2.92 points, p < 0.001) but not MMSE scores in patients undergoing AF catheter ablation compared to medical therapy. In addition, the maintenance of sinus rhythm was identified as a significant factor in dementia rate and improvement of MMSE and MOCA scores observed post catheter ablation therapy. Conclusion: AF catheter ablation may reduce the incidence of dementia and improve cognitive function. A large-scale randomized control trial is warranted before recommendations can be made regarding AF ablation and cognitive outcomes. Abstract Figure.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.032 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".