Abstract 18226: Finding the Ideal Biomaterial for Aortic Valve Repair
Bibliographic record
Abstract
Objectives: Cusp replacement in aortic valve repair (AVr) is associated with increased long-term repair failure. We measured hemodynamic and biomaterial properties after porcine AVr with 4 types of clinically relevant biomaterials to ascertain which material(s) would be best suited for repair. Methods: Porcine aortic roots with intact aortic valves were placed in a left heart simulator mounted with a high-speed camera for baseline valve assessment. The non-coronary cusp (NCC) was excised and replaced with autologous porcine pericardium (APP), glutaraldehyde-fixed bovine pericardial patch (BPP; Synovis™), extracelluar matrix scaffold (CorMatrix™), or collagen-impregnated Dacron (HEMASHIELD™). Biomaterial properties, along with St. Jude Medical™ Pericardial Patch with EnCapTM Technology (SJM), were determined and finite element modeling of the aortic valve and root complex were constructed to determine hemodynamic characteristics and leaflet stresses. Results: Post-repair geometric orifice areas were significantly reduced in the HEMASHIELD™ (5.06 cm2 [4.24-5.73];P<0.05), and CorMatrix™ ( 5.27 cm2 [4.57-5.56]; P=0.0001) groups when compared to unrepaired valves (6.08 cm2 [5.82-6.83]). Finite element modeling of biomaterials displayed differences in percent changes in total Von Mises stress for both repaired (NCC) and non-repaired left and right cusps with SJM (+4%,+24%) and APP (+5,+26%) having lower percent changes than BPP (+12%,+27%), HEMASHIELD™ (+30%,+9%), and CorMatrix™ (+13%,+32%) when compared to unrepaired valve stresses (Table 1). Conclusions: Due to increased stresses found in bovine pericardial patch, HEMASHIELD™, and CorMatrix™ groups, these biomaterials may be associated with late repair failure in AVr. Finally, autologous porcine pericardium and St. Jude Medical™ Pericadial Patch have the closest profile to normal aortic valves; therefore, use of either biomaterial may be best suited.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".