Twelve-month outcomes of the TaurusOne valve for transcatheter aortic valve implantation in patients with severe aortic stenosis
Bibliographic record
Abstract
BACKGROUND: In the last decade, transcatheter aortic valve implantation (TAVI) has developed rapidly in China. As TAVI progresses towards low surgical risk patients, the total number of TAVI procedures will grow exponentially. There is a need to develop a domestic TAVI device designed for Chinese patients. AIMS: The aim of this study was to evaluate the safety and efficacy of a self-expanding valve (TaurusOne transcatheter aortic valve system) in the treatment of patients with symptomatic severe aortic stenosis in China. METHODS: A prospective, multicentre, single-arm study was designed to enrol 120 patients with symptomatic severe aortic stenosis undergoing TAVI using the TaurusOne valve. The primary endpoint was all-cause mortality at one year. RESULTS: From September 2017 to April 2019, 120 patients were enrolled (35% bicuspid aortic valve, mean Society of Thoracic Surgeons [STS] score 9.95%). One-year mortality in 120 patients (follow-up rate, 100%), was 6.7% (upper 95% confidence interval: 12.9%), which was significantly lower than the performance goal of 30% (p<0.0001). All stroke, myocardial infarction, paravalvular leak ≥moderate, and new pacemaker implantation occurred in 4.4%, 1.8%, 0.8%, and 22.1% of patients, respectively, at one year. The haemodynamic results and quality of life scores also improved significantly. Patients with a bicuspid valve had similar outcomes to those with a tricuspid aortic valve. CONCLUSIONS: The one-year clinical results confirm the safety and efficacy of the TaurusOne transcatheter aortic valve system in the treatment of patients with symptomatic severe tricuspid and bicuspid aortic stenosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".