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Abstract 4371603: Cerebral Embolic Protection in TAVI: Does It Improve Outcomes? A Comprehensive Meta-Analysis and Trial Sequential Analysis

2025· article· en· W4415795150 on OpenAlexaboutno aff
Muhammad Faizan Ali, Khawaja Abdul Rehman, Mohamed Fawzi Hemida, Ashraf Ahmed, Husnain Ahmad, Sherif Eltawansy, Mohammad Hamza Bin Abdul Malik, Hassan Mehdi

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Randomized controlled trialStatistical significanceClinical trialAdverse effectPairwise comparisonStatistical analysisIschemic stroke

Abstract

fetched live from OpenAlex

Background: Previous evidence from randomized controlled trials (RCTs) on cerebral embolic protection (CEP) during transcatheter aortic valve implantation (TAVI) has been inconclusive. The recent PROTECT TAVI trial, the largest RCT to date, offers new data to reassess outcomes. We conducted a comprehensive meta-analysis with trial sequential analysis (TSA) to provide an up-to-date evaluation of the clinical impact of CEP in TAVI patients. Research question: Does the use of CEP improve clinical outcomes, including all-cause mortality and stroke, in patients undergoing TAVI who are at increased risk for these adverse events? Methods: A comprehensive search of databases was conducted to identify RCTs. Pairwise meta-analyses were performed using a random-effects model. Moreover, TSA was employed to calculate the required information size and construct monitoring boundaries for statistical significance and futility, assuming a two-sided alpha of 5% and 90% power. All statistical analyses were carried out using R software. Results: Eight RCTs encompassing a total of 11,666 patients were included, of whom 5,986 received CEP devices and 5,680 did not. Pairwise meta-analysis demonstrated no significant differences between two groups in terms of all-cause mortality (RR: 1.09; 95% CI: 0.75–1.56), all stroke (RR: 0.92; 95% CI: 0.75–1.14), disabling stroke (RR: 0.80; 95% CI: 0.52–1.21), life-threatening or disabling bleeding (RR: 0.95; 95% CI: 0.17–5.32), major vascular complications (RR: 1.22; 95% CI: 0.43–3.45), worsening of the NIHSS score (RR: 1.21; 95% CI: 0.70–2.10), presence of ischemic brain lesions (RR: 1.00; 95% CI: 0.93–1.07), and acute kidney injury (RR: 0.96; 95% CI: 0.39–2.36). However, use of CEP was associated with a statistically significant reduction in the risk of worsening Montreal Cognitive Assessment (MoCA) scores (RR: 0.72; 95% CI: 0.57–0.90; P = 0.01). TSA showed that the cumulative evidence for all stroke, and disabling stroke did not reach the required information size, indicating insufficient evidence to confirm a statistically significant benefit of CEP in reducing these outcomes. However, futility boundary was reached for all-cause mortality. Conclusion: While CEP did not significantly impact major clinical outcomes, it was associated with improved cognitive preservation. TSA indicated that evidence for reducing all stroke, and disabling stroke remains inconclusive due to insufficient information size. Further high-quality RCTs are warranted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.043
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.081
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.044
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.052
GPT teacher head0.375
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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