The use of a rigid instrument prior to stentless valve implantation facilitates correct alignment of the prosthesis and native aortic valve apparatus.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: When correctly seated in the aortic position, stentless valves are associated with a relatively low transvalvular gradient. This leads to regression of left ventricular hypertrophy and long-term survival. The alleged complexity of stentless valve implantation has led to a preference for stented/mechanical prostheses. Here, the use of a rigid instrument to prevent technical complications after stentless valve implantation was investigated. METHODS: Aortic valve replacement was performed in 75 patients (44 males, 31 females; mean age 72 years; range: 33-89 years) using the Toronto Stentless Porcine Valve (TSPV). Among patients, 37% had coronary artery bypass grafting and 3% mitral valve replacement. Valve size was either 23-25 mm (65%) or 21 mm (35%) and determined by sinotubular junction diameter. A rigid instrument was designed that mimics actual valve shape and accounted for valve dimensional variations and asymmetries on a size-by-size basis. The instrument was used to mark the site of the inflow and outflow suture lines and to determine orientation of the muscle bar on the prosthetic valve. Intraoperative transesophageal echocardiography was used to monitor all patients. RESULTS: The mean intraoperative mean systolic peak pressure gradient (all valves) was 18.35 +/- 9.41 mmHg; there were no paravalvular leaks. Among patients, 22% had central trace aortic insufficiency, and one patient developed renal failure that required hemodialysis. There were no cerebral vascular accidents/infections, but one perioperative myocardial infarction occurred. There were four postoperative deaths, but none was valve-related. CONCLUSION: Routine use of the instrument may avoid many risks during TSPV implantation. The device permits the surgeon to accommodate variation in the angle between the coronary ostia, as well as in the distance between these ostia and the native annulus.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".