Does catheter ablation for atrial fibrillation increase or reduce neurological insult?
Bibliographic record
Abstract
PURPOSE OF REVIEW: This article will review the periprocedural and long-term risk of stroke and other adverse neurological outcomes in patients having catheter ablation of atrial fibrillation. RECENT FINDINGS: Randomized trials of medication-based rhythm control for atrial fibrillation have failed to demonstrate a reduction in stroke. There is hope that catheter ablation of atrial fibrillation may provide such a benefit; however, definitive clinical trials have yet to be completed. It is well established that catheter ablation of atrial fibrillation is associated with a risk of periprocedural stroke; however, new studies using magnetic resonance imaging suggest that silent cerebral infarction is 10 times more common than clinical stroke. Studies which have systematically screened for silent cerebral infarction have been invaluable in refining the technique of atrial fibrillation catheter ablation, by identifying procedural details and ablation technologies which are more likely to result in this surrogate outcome. There is also early suggestion that these silent infarctions may be associated with longer-term adverse neuropsychological outcomes. SUMMARY: A more precise understanding of neurological injury with catheter ablation of atrial fibrillation is helping to refine this technique and will ultimately help determine if the prevention of recurrent atrial fibrillation with catheter ablation can reduce the risk of stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".