Beating‐heart percutaneous mitral valve repair using a transcatheter endovascular suturing device in an animal model
Bibliographic record
Abstract
BACKGROUND: The edge-to-edge (Alfieri) technique for mitral valve repair is a versatile method of treating mitral insufficiency. Because of its simplicity, it has been applied in minimally invasive surgery, and recently, in the design of endovascular closed-heart devices. AIM: The purpose of this study was to evaluate the acute in-vivo safety and feasibility of a novel percutaneous mitral valve repair system based on Alfieri technique in an animal model. METHODS: Under general anesthesia, 11 pigs (90-100 kgs), underwent percutaneous Alfeiri procedure. The right femoral vein was punctured and the mitral valve was approached via a standard transeptal puncture. Combined intracardiac echo and fluoroscopic guidance was used. The procedure included: the positioning of a guide catheter for multiple access to the left atrium and for directing devices; the use of a therapy device to capture the free edge of the mitral valve leaflets using vacuum, and to deliver the suture to the valve and finally the fixation with a Nitinol suture clip, and trimming of the suture with a fastener catheter. RESULTS: Leaflet capture, suture placement, and suture-clip deployment was successful in all 11 animals. There were no acute cardiac or access site complications. Procedural time (from wire in left atrium to completion of the procedure was 18 +/- 9 min (range 9-30 min). Blood loss was 67 +/- 44 ml (range 0-125 ml). A double orifice configuration was visible by echocardiography at the end of the procedure in all animals. CONCLUSION: This acute animal study demonstrated the feasibility of a beating heart percutaneous Alfieri procedure in a non-diseased porcine valve using an endovascular suturing device to safely access the mitral valve, place a stitch through the mitral valve leaflets, and deploy a suture-clip that reproduces the surgical technique. Clinical application of this device in humans needs to be evaluated.
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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 | 0.020 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".