Addressing Peri-Device Leaks in Next-Generation Transcatheter Left Atrial Appendage Occluders: An Open Question
Bibliographic record
Abstract
With FDA-approved devices, left atrial appendage (LAA) occlusion has emerged as a well-established and rapidly growing approach to stroke prevention in patients with non-valvular atrial fibrillation. These devices are indicated for use in patients who are at increased risk of stroke and systemic embolism, as determined by CHA2DS2-VASc scores, and are suitable for anticoagulation therapy, with an appropriate rationale for seeking a non-pharmacologic alternative. This includes patients who may be unsuitable for long-term anticoagulation due to contra-indications. These devices, generally consisting of a nitinol-framed structure with a circular cross-section, are positioned within the LAA to obstruct the ostium, effectively preventing the thrombus from embolizing the brain. The initial clinical data from pivotal trials and observational registries indicated no strong correlation between peri-device leaks (PDLs) and adverse events. However, recent studies have shown that PDLs are associated with a higher risk of thrombo-embolic events, leading to renewed interest in managing PDLs. This paper reviews the occurrence of PDLs after percutaneous LAA occlusion using current FDA-approved devices, highlighting the need for non-circular occluders to better-accommodate the inherent variability in LAA anatomy. It also compares the benefits and limitations of emerging approaches still under investigation, focusing on addressing PDLs.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".