Initial clinical experience with VersaCross transseptal system for transcatheter mitral valve repair
Bibliographic record
Abstract
OBJECTIVES: The aim of this study is to describe the initial experience with versacross transseptal (TS) system for transseptal puncture for the transcatheter mitral valve repair using the MitraClip device. BACKGROUND: Transeptal puncture is a key step in transcatheter mitral valve repair (MVR) and the use of the VersaCross system comprised of a sheath, a dilator and a radiofrequency wire has not been previously described. METHODS: Prospective single center study of consecutive patients undergoing transcatheter mitral valve repair with the MitraClip device were included. Targeted TS puncture was performed under transesophageal echocardiographic (TEE) guidance. Baseline demographics, procedural characteristics, and major adverse procedural events were collected. RESULTS: Twenty-five consecutive patients underwent transseptal puncture using the VersaCross TS system. Transseptal puncture was successful in 100% of patients. The mean time for TS puncture was 3 3 ± 1.6 min with no major adverse procedural events. The mean time from insertion of the VersaCross system to insertion of the MitraClip guide catheter was 3.8 ± 3.0 minutes. CONCLUSION: The VersaCross TS system was successful in all patients for MitraClip procedure with no adverse procedural events and may be associated with increased procedural efficiency.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".