Cerebral Embolic Protection Devices for the Prevention of Stroke in Patients Undergoing Transcatheter Aortic Valve Implantation: An Updated Meta‐Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Stroke remains one of the most devastating complications following transcatheter aortic valve implantation (TAVI). Although cerebral embolic protection devices (CEPDs) have emerged to mitigate patients' risks, their impact on stroke risk, as well as other clinical and neurocognitive outcomes after TAVI, remains uncertain. We aimed to assess whether CEPDs alleviate stroke risks and neurocognitive outcomes after TAVI. We systematically searched MEDLINE, Scopus, Web of Science (WOS), and the Cochrane CENTRAL from inception until May 2025. We included randomized controlled trials (RCTs) that assessed the effectiveness of CEPD compared to the control group (no CEPD) in adult patients (> 18 years) undergoing TAVI. The primary endpoint was the incidence of all-cause stroke. In contrast, the secondary endpoints included disabling stroke, systemic bleeding, transient ischemic attack (TIA), and major adverse cardiovascular and cerebrovascular events (MACCE). Additionally, we assessed neurological outcomes, including changes in the Montreal Cognitive Assessment (MoCA) score, the National Institutes of Health Stroke Scale (NIHSS) score, and the presence of new ischemic lesions. Nine RCTs comprising 11,696 patients were included in the final analysis. The use of CEPDs showed no statistical difference in reducing all-cause stroke compared to the control group (OR = 0.91, 95% CI [0.73-1.15], p = 0.44). Additionally, there was no significant difference in other studies' secondary outcomes, including disabling stroke, MACCE, systemic bleeding, or neurological outcomes, such as worsening NISSS, decline in MoCA score, and the presence of new ischemic lesions. The use of CEPD during TAVI showed no benefit in reducing the risks of all-cause stroke and other neurological outcomes studied.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".