Frequency, Impact, and Predictors of Access Complications With Plug-Based Large-Bore Arteriotomy Closure - A Patient-Level Meta-Analysis
Bibliographic record
Abstract
BACKGROUND/PURPOSE: The MANTA is a dedicated plug-based large-bore vascular closure device (VCD) providing safe hemostasis in most patients, but data on the clinical impact and mechanisms of MANTA related complications are limited. This study sought to determine the frequency, impact and predictors of MANTA-related access complications. METHODS/MATERIALS: This patient-level meta-analysis included data from 2 medical device approval studies and 1 post-approval registry. The primary endpoint was the composite of major and minor access complications. Technical success was defined as hemostasis with MANTA closure device without need for vascular surgery or stenting. RESULTS: Eight hundred ninety-one patients (mean age 80) underwent transcatheter aortic valve replacement (n = 814), endovascular aortic repair (n = 71), balloon aortic valvuloplasty (n = 4) or mechanical circulatory support (n = 2). Technical success was 96.4% and median time to hemostasis was 31 (interquartile range: 17-76) seconds. The primary endpoint occurred 9.1% and bailout vascular surgery or stenting was necessary in 32 patients (3.6%). Female gender (OR: 2.63, CI: 1.46-4.73, p = 0.001), left femoral access (OR: 2.18, CI: 1.17-4.06, p = 0.015) and unfavorable arteriotomy phenotype (combination of a small femoral artery diameter with a deep arteriotomy; OR 2.27: 1.26-4.10, p = 0.006) independently predicted access complications. Access complications most often consisted of vessel dissection, stenosis or occlusion and predominantly occurred in patients with an unfavorable arteriotomy phenotype. CONCLUSIONS: Large-bore arteriotomy closure with MANTA VCD provided fast and safe hemostasis with an acceptable complication rate. Refined procedure planning and risk-stratification may further improve MANTA VCD performance.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.035 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".