Transcatheter Aortic Valve Implantation
Bibliographic record
Abstract
BACKGROUND: Transcatheter aortic valve implantation is an alternative to open heart surgery in patients with aortic stenosis. However, long-term data on a programmatic approach to aortic valve implantation remain sparse. METHODS AND RESULTS: Transcatheter aortic valve implantation was performed in 168 patients (median age, 84 years) in the setting of severe aortic stenosis and high surgical risk. Access was transarterial (n=113) or, in the presence of small iliofemoral artery diameter, transapical (n=55). The overall success rate was 94.1% in this early experience. Intraprocedural mortality was 1.2%. Operative (30-day) mortality was 11.3%, lower in the transarterial group than the transapical group (8.0% versus 18.2%; P=0.07). Overall mortality fell from 14.3% in the initial half to 8.3% in the second half of the experience, from 12.3% to 3.6% (P=0.16) in transarterial patients and from 25% to 11.1% (P=0.30) in transapical patients. Functional class improved over the 1-year postprocedure period (P<0.001). Survival at 1 year was 74%. The bulk of late readmission and mortality was not procedure or valve related but rather was due to comorbidities. Paravalvular regurgitation was common but generally mild and remained stable at late follow-up. At a maximum of >3 years and a median of 221 days, structural valve failure was not observed. CONCLUSIONS: Transcatheter aortic valve implantation can result in early and sustained functional improvement in high-risk aortic stenosis patients. Late outcome is determined primarily by comorbidities unrelated to aortic valve disease.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".