Bibliographic record
Abstract
Aortic Stenosis (AS) is the most common valvular heart disease. Aortic valve replacement (AVR) is the only acceptable treatment for AS. Several replacement methods are available to treat AS including conventional surgical aortic valve replacement (SAVR), transcatheter aortic valve replacement (TAVR), and Sutureless aortic valve replacement (SuAVR). SAVR showed excellent long-term results. However, it is an invasive procedure and is denied in substantial number of patients. TAVR showed excellent results and outcomes when compared to SAVR. However, it is associated with increased rate of paravalvular leaks that may impact long term outcomes. SuAVR has developed to overcome the drawbacks of SAVR and TAVR. SuAVR is associated with favorable short and midterm outcomes when compared to SAVR and TAVR. In this thesis, we summarize the safety, the evidence and the perceptions of using SuAVR in Canada. In Chapter1, we evaluated the use of SuAVR Perceval bioprosthesis in retrospective single center study of 415 patients with AS. SuAVR showed excellent immediate post-operative and hemodynamics outcomes. In chapter 2, we sought to establish perceptions and patterns to SuAVR use among Canadian cardiac surgeons. Sixty-Six Canadian cardiac Surgeons responded to the survey. Surgeons reported influential factors, barriers to use SuAVR, and their interest in a trial comparing SuAVR versus TAVR. Surgeons were likely to use SuAVR in high risk patients with hostile aortic root, small aortic annulus and in patients undergoing concomitant procedures whereas cost was the main limiting factor to use SuAVR in Canada. Majority of surgeons reported their interest in participating in a trial comparing SuAVR with TAVR. In chapter 3, we systematically reviewed and meta-analyzed the international evidence of using SuAVR versus SAVR and TAVR. SuAVR showed favorable or comparable results to SAVR and TAVR. However, long term and randomized data are needed to confirm these results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".