Leaflet modification before transcatheter aortic valve implantation in patients at risk for coronary obstruction: the ShortCut study
Bibliographic record
Abstract
BACKGROUND AND AIMS: This trial sought to assess the safety and efficacy of ShortCut, the first dedicated leaflet modification device, prior to transcatheter aortic valve implantation (TAVI) in patients at risk for coronary artery obstruction. METHODS: This pivotal prospective study enrolled patients with failed bioprosthetic aortic valves scheduled to undergo TAVI and were at risk for coronary artery obstruction. The primary safety endpoint was procedure-related mortality or stroke at discharge or 7 days, and the primary efficacy endpoint was per-patient leaflet splitting success. Independent angiographic, echocardiographic, and computed tomography core laboratories assessed all images. Safety events were adjudicated by a clinical events committee and data safety monitoring board. RESULTS: Sixty eligible patients were treated (77.0 ± 9.6 years, 70% female, 96.7% failed surgical bioprosthetic valves, 63.3% single splitting and 36.7% dual splitting) at 22 clinical sites. Successful leaflet splitting was achieved in all [100%; 95% confidence interval (CI) 94%-100.0%, P < .001] patients. Procedure time, including imaging confirmation of leaflet splitting, was 30.6 ± 17.9 min. Freedom from the primary safety endpoint was achieved in 59 [98.3%; 95% CI (91.1%-100%)] patients, with no mortality and one (1.7%) disabling stroke. At 30 days, freedom from coronary obstruction was 95% (95% CI 86.1%-99.0%). Within 90 days, freedom from mortality was 95% [95% CI (86.1%-99.0%)], without any cardiovascular deaths. CONCLUSIONS: Modification of failed bioprosthetic aortic valve leaflets using ShortCut was safe, achieved successful leaflet splitting in all patients, and was associated with favourable clinical outcomes in patients at risk for coronary obstruction undergoing TAVI.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".