Combined use of suture and plug-based devices for femoral access hemostasis and vascular outcomes in transcatheter aortic valve replacement: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Transcatheter Aortic Valve Replacement (TAVR) is the preferred treatment for severe aortic stenosis. However, vascular complications and bleeding remain common after transfemoral TAVR, impacting outcomes. While suture-based and plug-based vascular closure devices (VCDs) are used, a combined suture and plug-based approach may offer benefits. Purpose This study compares the effectiveness of dual suture-based arterial closure versus combined suture and plug-based closure in achieving hemostasis after TAVR. Methodology A systematic search of PubMed, Web of Science, and Embase was conducted until October 2024. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool for randomized controlled trials and the Newcastle-Ottawa Scale for cohort studies. Data analysis was performed using Review Manager version 5.4, with pooled outcomes reported as risk ratios or mean differences (MD) with 95% confidence intervals (CI). Results The meta-analysis included up to 2,304 patients across multiple studies. Major vascular bleeding (RR: 0.72, 95% CI: 0.39–1.34, p = 0.30) and minor vascular bleeding (RR: 0.86, 95% CI: 0.58–1.28, p = 0.47) showed no significant difference in the two groups. However, the suture plus plug-based vascular closure device significantly reduced major vascular complications by 50% (RR: 0.50, 95% CI: 0.33–0.76, p = 0.001) and minor vascular complications by 30% (RR: 0.70, 95% CI: 0.51–0.96, p = 0.03). VCD failure was 74% lower (RR: 0.26, 95% CI: 0.15–0.47, p < 0.00001) in the suture plus plug-based group and unplanned interventions showed no significant difference (RR: 0.68, 95% CI: 0.38–1.22, p = 0.19) in this group. Conclusion The suture plus plug-based VCD demonstrated superiority over dual suture device by significantly reducing vascular complications and device failure incidents.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.007 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".