Clinical Aspects and Current Evidence Base for Transcatheter Aortic Valve Implantation
Bibliographic record
Abstract
Aortic stenosis (AS) is a common disorder that affects nearly 5% of individuals over 75 years of age. Many patients with AS are unable to undergo surgical valve replacement (SAVR) as they are commonly deemed to be of very high risk. Transcatheter aortic valve implantation (TAVI), introduced in 2002, is a new method for treatment of these patients. Computed tomography (CT) is becoming the gold standard imaging modality for preprocedural planning, including assessment of annular size and access. Since 2002, >100,000 procedures have been performed with either a balloon-expandable valve (Edwards SAPIEN valve) or the self-expanding valve (Medtronic CoreValve). A growing body of evidence supporting the effectiveness and safety of TAVI includes the PARTNER trial and the CoreValve pivotal trial. These have found significantly better survival for the TAVI arm compared with SAVR (CoreValve). There were no significant differences in all-cause mortality between TAVI and SAVR, whereas significantly reduced all-cause mortality was observed for TAVI when compared with standard therapy (PARTNER). Paravalvular regurgitation is increased in TAVI compared with SAVR; however, integration of CT into valve selection has shown to improve outcomes. There is conflicting evidence regarding increased risk for stroke after TAVI, and occurrence of conduction disturbances and the need for a pacemaker after TAVI remain a concern. Upcoming trials are focusing on assessing outcomes for use of TAVI in intermediate-operative risk patients. The future will likely include an increased choice of devices, smaller access sites, and further integration of CT for preprocedure planning.
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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 | 0.010 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".