Outcomes following bioprosthetic valve replacement in prior non‐cardiac transplant recipients
Bibliographic record
Abstract
BACKGROUND: We report on overall survival and valve-related outcomes after bioprosthetic valve replacement in prior transplant recipients. METHODS: From January 2004 to December 2018, 20 consecutive patients (mean age 65.7-years, 90% male) with prior non-cardiac transplantation underwent bioprosthetic aortic (n = 18) or combined aortic and mitral (n = 2) valve replacement. Patients consisted of kidney (n = 14), lung (n = 2), liver (n = 3), and bone-marrow (n = 2) transplants with the most common indication for valve replacement being calcific degeneration (n = 12). Outcomes were measured over a 12-year span, with a median follow-up duration of 3.9 years. RESULTS: Overall survival at 30 days was 100% and at median follow-up was 60%. Acute kidney injury occurred in 50% (n = 10) with temporary dialysis required in 5% (n = 1) and 15% (n = 3) suffered respiratory failure. No patients experienced major bleeding, heart failure, or sternal wound infection. No patients required redo valve replacement during the study period. CONCLUSIONS: Our results provide contemporary data demonstrating that patients with prior transplant can undergo bioprosthetic valve replacement with acceptable inhospital mortality rates and long-term survival, with a low rate of major morbidity. Furthermore, bioprosthetic valve replacement is a viable option in this group of patients with no redo valve replacement and acceptable long-term hemodynamic valvular function.
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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 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".