Initial experience with xenograft bioconduit for the treatment of complex prosthetic valve endocarditis
Bibliographic record
Abstract
INTRODUCTION: The treatment of complex prosthetic valve endocarditis (PVE) with aortic root abscess remains a surgical challenge. Several studies support the use of biological tissues to minimize the risk of recurrent infection. We present our initial surgical experience with the use of an aortic xenograft conduit for aortic valve and root replacement. METHODS: Between October 2013 and August 2015, 15 xenograft bioconduits were implanted for complex PVE with abscess (13.3% female). In 6 patients, concomitant procedures were performed: coronary bypass (n=1), mitral valve replacement (n=5) and tricuspid annuloplasty (n=1). The mean age at operation was 60.3±15.5 years. The mean Logistic European system for cardiac operating risk evaluation (EuroSCORE) was 46.6±23.6. The median follow-up time was 607±328 days (range: 172-1074 days). RESULTS: There were two in-hospital deaths (14.3% mortality), two strokes (14.3%) and seven patients required permanent pacemaker insertion for conduction abnormalities (46.7%). The mean length of hospital stay was 26 days. At pre-discharge echocardiography, the conduit mean gradient was 9.3±3.3mmHg and there was either none (n=6), trace (n=6) or mild aortic insufficiency (n=1). There was no incidence of mid-term death, prosthesis-related complications or recurrent endocarditis. CONCLUSIONS: Xenograft bioconduits may be safe and effective for aortic valve and root replacement for complex PVE with aortic root abscess. Although excess early mortality reflects the complexity of the patient population, there was good valve hemodynamics, with no incidence of recurrent endocarditis or prosthesis failure in the mid-term. Our data support the continued use and evaluation of this biological prosthesis in this high-risk patient cohort.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".