Cerebral Embolic Protection Devices During Transcatheter Aortic Valve Implantation
Bibliographic record
Abstract
Background and Purpose— Silent ischemic embolic lesions are common after transcatheter aortic valve implantation (TAVI). The use of embolic protection devices (EPD) may reduce the occurrence of these embolic lesions. Thus, a quantitative overview and credibility assessment of the literature was necessary to draw a robust message about EPD. Therefore, the aim of this meta-analysis was to study whether the use of EPD reduces silent ischemic and clinically evident cerebrovascular events associated with TAVI. Methods— We conducted a comprehensive search to identify studies that evaluated patients undergoing TAVI with or without EPD. Random-effects meta-analyses were performed to estimate the effect of EPD compared with no-EPD during TAVI using aggregate data. Results— Sixteen studies involving 1170 patients (865/305 with/without EPD) fulfilled the inclusion criteria. The EPD delivery success rate was reported in all studies and was achieved in 94.5% of patients. Meta-analyses evaluating EPD versus without EPD strategies could not confirm or exclude any differences in terms of clinically evident stroke (relative risk, 0.70; 95% confidence interval [CI], 0.38–1.29; P =0.26) or 30-day mortality (relative risk, 0.58; 95% CI, 0.20–1.64; P =0.30). There were no significant differences in new-single, multiple, or total number of lesions. The use of EPD was associated with a significantly smaller ischemic volume per lesion (standardized mean difference, −0.52; 95% CI, −0.85 to −0.20; P =0.002) and smaller total volume of lesions (standardized mean difference, −0.23; 95% CI, −0.42 to −0.03; P =0.02). Subgroup analysis by type of valve showed an overall trend toward significant reduction in new lesions per patient using EPD (standardized mean difference, −0.41; 95% CI, −0.82 to 0.00; P =0.05), driven by self-expanding devices. Conclusions— The use of EPD during TAVI may be associated with smaller volume of silent ischemic lesions and smaller total volume of silent ischemic lesions. However, EPD may not reduce the number of new-single, multiple, or total number of lesions. There was only very low quality of evidence showing no significant differences between patients undergoing TAVI with or without EPD with respect to clinically evident stroke and mortality.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.016 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".