Data on plug-based large-bore arteriotomy vascular closure device related access complications
Bibliographic record
Abstract
This article provides supplementary tables and figures to the research article: Frequency, Impact and Predictors of Access Complications with Plug-Based Large-Bore Arteriotomy Closure - A patient level meta-analysis [1]. The data provide insight in the type and management of access complications related to the plug-based MANTA vascular closure device (VCD) for large-bore catheter-based cardiovascular interventions. Since MANTA is mostly used in transcatheter aortic valve replacement (TAVR) procedures, this article also contains a sub-group analysis on TAVR procedures using contemporary valve-platforms. Further, data describing MANTA hemostasis times and mortality causes are included. For this dataset, individual patient data were derived from a European and a North American device approval study (the Conformite Européene [CE] mark study and the investigational device exemption SAFE-MANTA study [2,3]) in addition to a post-approval registry (the MARVEL registry [4]) covering a total of 891 patients who were enrolled between 2015 and 2019 across 28 investigational sites. Eligibility criteria were most stringent in the SAFE MANTA study (38% of patients) whereas the MARVEL registry applied liberal and only relative exclusion criteria (56% of patients). A total of 78 Roll-in cases (i.e. first or second time operator use of the MANTA VCD) who were excluded from analysis in SAFE MANTA were included in the present to evaluate a potential learning curve effect. Therefore, this dataset reflects the largest study population undergoing arteriotomy closure with the MANTA VCD by operators at various levels of experience, which can be valuable to further build on research regarding percutaneous large-bore arteriotomy management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".