Early and late outcomes after cardiac retransplantation
Bibliographic record
Abstract
BACKGROUND: Cardiac retransplantation remains the most viable option for patients with allograft heart failure; however, careful patient selection is paramount considering limited allograft resources. We analyzed clinical outcomes following retransplantation in an academic, tertiary care institution. METHODS: Between 1981 and 2011, 593 heart transplantations, including 22 retransplantations were performed at our institution. We analyzed the preoperative demographic characteristics, cause of allograft loss, short- and long-term surgical outcomes and cause of death among patients who had cardiac retransplantations. RESULTS: Twenty-two patients underwent retransplantation: 10 for graft vascular disease, 7 for acute rejection and 5 for primary graft failure. Mean age at retransplantation was 43 (standard deviation [SD] 15) years; 6 patients were women. Thirteen patients were critically ill preoperatively, requiring inotropes and/or mechanical support. The median interval between primary and retransplantation was 2.2 (range 0-16) years. Thirty-day mortality was 31.8%, and conditional (> 30 d) 1-, 5- and 10-year survival after retransplantation were 93%, 79% and 59%, respectively. A diagnosis of allograft vasculopathy (p = 0.008) and an interval between primary and retransplantation greater than 1 year (p = 0.016) had a significantly favourable impact on 30-day mortality. The median and mean survival after retransplantation were 3.3 and 5 (SD 6, range 0-18) years, respectively; graft vascular disease and multiorgan failure were the most common causes of death. CONCLUSION: Long-term outcomes for primary and retransplantation are similar if patients survive the 30-day postoperative period. Retransplantation within 1 year of the primary transplantation resulted in a high perioperative mortality and thus may be a contraindication to retransplantation.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".