Dedicated plug based closure for large bore access –The MARVEL prospective registry
Bibliographic record
Abstract
OBJECTIVES: To study safety and performance of the MANTA Vascular closure device (VCD) under real world conditions in 10 centers. BACKGROUND: The MANTA is a novel plug-based device for large bore arteriotomy closure. METHODS: We included all eligible patients who underwent transfemoral large bore percutaneous procedures. Exclusion criteria were per operator's discretion and included severe calcification or marked tortuosity of the access vessel, presence of marked obesity/cachexia or a systolic blood pressure above 180 mmHg. The primary performance endpoint was time to hemostasis. Primary and secondary safety endpoints were major and minor access site related vascular complications up to 30 days, respectively. Vascular complications were adjudicated by an independent clinical event committee according to VARC-2 criteria. We performed multivariable logistic regression to estimate the effect of baseline and procedural characteristics on any and major vascular complications. RESULTS: Between February 2018 and July 2019 500 patients were enrolled undergoing Transcatheter aortic valve replacement (TAVR, N = 496), Balloon aortic valvuloplasty (BAV, N = 2), Mechanical circulatory support (MCS, N = 1) or Endovascular aneurysm repair (EVAR, N = 1). Mean age was 80.8 ± 6.6 years with a median STS-score of 2.7 [IQR 2.0-4.3] %. MANTA access site complications were major in 20 (4%) and minor in 28 patients (5.6%). Median time to hemostasis was 50 [IQR 20-120] sec. Severe femoral artery calcification, scar presence in groin, longer procedure duration, female gender and history of hypertension were independent predictors for vascular complications. CONCLUSION: In this study, MANTA appeared to be a safe and effective device for large bore access closure under real-world conditions.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".