Importance of anticoagulation and postablation silent cerebral lesions: Subanalyses of REVOLUTION and reMARQable studies
Bibliographic record
Abstract
Abstract Background Silent cerebral lesions (SCLs) are a potential complication of left atrial radiofrequency ablation (RFA) procedures for paroxysmal atrial fibrillation (PAF). We aimed to compare the incidence of SCLs in patients treated with irrigated RFA multielectrode catheters (nMARQ® Catheter group) and irrigated focal RFA catheters (NAVISTAR® THERMOCOOL® Catheter; TC group) after PAF ablation from subpopulation neurological assessment (SNA) cohorts of the REVOLUTION and reMARQable studies. Methods Data from SNA cohorts in the prospective, nonrandomized REVOLUTION study (March 2011–September 2013) and the prospective, randomized, controlled reMARQable study (October 2013–November 2015) were included. The incidence of SCLs was assessed pre‐ and postablation using magnetic resonance imaging. Neurological deficits were assessed using the National Institutes of Health Stroke Scale, modified Rankin Scale, and Montreal Cognitive Assessment. Results A total of 37 patients from REVOLUTION and 76 patients from reMARQable were included in the SNA cohort of each study. In the REVOLUTION SNA cohort, the incidence of SCLs was 21.1% (4/19) in the nMARQ® Catheter group and 5.9% (1/17) in the TC group. Findings from REVOLUTION helped inform the reMARQable study protocol's stringent anticoagulation regimen. SCL incidence was subsequently reduced in both groups (nMARQ® Catheter, 7.9%; TC, 3.3%). No permanent neurological deficits were observed. Conclusion Adherence to a stringent anticoagulation regimen prior to and during ablation procedures appears to be an important factor in minimizing the risk of SCL.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".