P487Incidence of brain lesions after percutaneous catheter-based left atrial appendage closure as detected by MRI
Bibliographic record
Abstract
Background: Percutaneous catheter-based left atrial appendage closure (LAAC) is an increasingly performed procedure with the aim to prevent strokes and systemic embolisations in patients with atrial fibrillation (AF) and is considered in particular in patients at high risk of bleeding with oral anticoagulation. Purpose: The present prospective study aims to evaluate the incidence of magnetic resonance imaging (MRI)-detected brain lesions as well as potential changes of neurocognitive functions after percutaneous LAAC in patients with AF. Methods: Brain MRI at 3 Tesla was performed within 24 hours before and after LAAC. A neurocognitive examination using the National Institutes of Health Stroke Scale (NIHSS) score and the Montreal Cognitive Assessment (MoCA) Test was performed in all patients: Results: Successful device implantation was achieved in all patients (n=16; age 74±11.5 years, male=12) using the Amulet (n=11), Occlutech (n=3) or a Lambre (n=2) device. Mean procedure time was 58±12.3 minutes. While no new-onset neurological deficits were observed after LAAC, novel brain lesions were detected by MRI in 8/16 (50%) patients after LAAC. Compared to pre-LAAC assessment, the mean post-LAAC MoCA test and mean NIHSS score revealed similar results. The MoCA test (24.0±4.8 vs 24.1±4.5; p=0.96) and the NIHSS score (1.0±1.6 vs 1.1±2.1; p=0.79) were similar between patients with or without new-onset brain lesions. Conclusion: While new MRI-detected brain lesions are commonly observed after percutaneous LAAC, the underlying mechanisms and clinical significance of this finding have yet to be determined. Importantly, no significant changes in neurological or neurocognitive functions were observed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".