A Comparison of Two Vascular Closure Strategies in Transcatheter Aortic Valve Replacement: Suture and Plug versus Suture Alone – A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Vascular complications following transcatheter aortic valve replacement (TAVR) significantly contribute to morbidity and mortality. Conventional suture-based closure technique has been widely utilized for large-bore arterial access closure. Recent findings on hybrid strategy combining plug and suture-based devices has been on spotlight as it may improve the hemostatic efficacy and lower the access-site related complications and clinical outcomes. METHODS: We performed a systematic review and meta-analysis of studies comparing a suture-based approach with a hybrid closure strategy (suture+plug) in aortic stenosis patients undergoing TAVR. Included studies were appraised following the Cochrane Risk of Bias and Newcastle-Ottawa Scale tools. Forest plots were extracted in Review Manager with a main outcome of pooled-risk ratio (RR). The primary endpoint was the composite of access-site related vascular complications as defined by Valve Academic Research Consortium criteria whilst secondary end-points were in-hospital bleeding, closure device failure, mortality, and unplanned endovascular or surgical intervention. RESULTS: Six eligible studies encompassing 2,064 patients were analyzed. Compared with suture-based closure, hybrid closure exhibited a lower rate of vascular complications (pooled-RR 0.46; 95% confidence interval [CI], 0.38-0.57; p < 0.001), closure device failure (pooled-RR 0.35; 95% CI, 0.13-0.96; p = 0.04), in-hospital bleeding events (pooled-RR 0.38; 95% CI, 0.26-0.55; p < 0.001), and mortality (pooled-RR 0.51; 95% CI, 0.26-0.99; p = 0.049). Unplanned endovascular or surgical intervention was no different among two groups (pooled-RR 0.42; 95% CI, 0.17-1.06; p = 0.07). CONCLUSION: Hybrid vascular closure strategy offers better efficacy with fewer complications amongst patients undergoing TAVR, directing the clinical adoption of hybrid techniques, although further large-scale multicenter studies are warranted to confirm the benefit and optimize patient selection.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.025 | 0.043 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".