The Ross procedure: biomechanical properties of the pulmonary artery according to aortic valve phenotype
Bibliographic record
Abstract
OBJECTIVES: The aim of this study is to determine whether patients undergoing the Ross procedure with bicuspid aortic valves have pulmonary artery biomechanical properties different from those with tricuspid valves. METHODS: Thirty-two pulmonary arteries and 20 aortas were obtained from patients undergoing the Ross procedure at the time of surgery, from a cohort of 32 patients. The aortic valve was tricuspid in 5 patients (16%), bicuspid in 18 patients (56%) and unicuspid in 9 patients (28%). Histological analysis and ex vivo equi-biaxial tensile testing completed within 8 hours of surgery were used to evaluate differences in patient groups and between the pulmonary artery and the ascending aorta. RESULTS: There was no difference in thickness among pulmonary arteries when compared according to aortic valve phenotype (P = 0.94). There was no difference in the tensile tissue properties among aortas and pulmonary arteries when compared according to aortic valve phenotype, in either the circumferential or longitudinal axis. When compared according to the main surgical indication, pulmonary artery walls from patients with pure aortic regurgitation were less stiff than their counterparts (aortic regurgitation: 0.055 ± 0.037 MPa, aortic stenosis: 0.103 ± 0.051 MPa, mixed disease: 0.110 ± 0.044 MPa and aortic valve endocarditis: 0.216 ± 0.033 MPa, P = 0.002). There was no difference in the number of elastic lamellae in pulmonary artery specimens from the three different aortic valve phenotypes, as well as in the aortic specimens. CONCLUSIONS: No significant differences were observed in the biomechanical properties of pulmonary arteries when compared according to aortic valve phenotype.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".