Bibliographic record
Abstract
he percutaneous treatment of valvular heart disease is rapidly progressing through clinical trials.For one valvular lesion, critical aortic stenosis, recent advances in technology and percutaneous techniques may potentially change the way in which we manage this disease in the most frail and elderly patients.Some of these new techniques blur the distinction between surgical and nonsurgical treatments.In this issue of Circulation, Lichtenstein and colleagues report the first series of patients to have an aortic valve implanted via a thoracotomy to expose the left ventricular apex, for subsequent sheath insertion, over-the-wire delivery system advancement, and image-guided implantation of a stent mounted equine crimped on a delivery balloon. 1 This article is seminal in defining 2 major emerging issues: valvular heart disease treatments that are hybrids of surgical and catheter-based techniques and the challenges inherent in determining what treatment modalities are best in the growing problem of aortic stenosis in mature, ie, elderly, adults.This report adds to the recently published report from the St. Paul's Hospital group in Vancouver using the retrograde percutaneous aortic valve (PAV) implantation technique.2 Article p 591Which patients will be appropriate for these new approaches to the treatment of aortic stenosis in the mature adult population?Timely assessment of the efficacy and safety of these techniques will be critical for patients, care providers, regulatory agencies, and insurers to evaluate for patientspecific decision making and healthcare policy.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".