Determinants of survival following heart transplantation in adults with congenital heart disease
Bibliographic record
Abstract
BACKGROUND: Adult patients surviving with congenital heart disease (ACHD) is growing. We examine the factors associated with heart transplant outcomes in this challenging population with complex anatomy requiring redo-surgeries. METHODS: We reviewed the United Network for Organ Sharing-Standard Transplant Analysis and Research database and analyzed 35,952 heart transplants from January 1st, 2000, to September 30th, 2018. We compared transplant characteristics for ischemic cardiomyopathy (ICM) (n = 14,236), nonischemic cardiomyopathy (NICM) (n = 20,676), and ACHD (n = 1040). Mean follow-up was 6.20 ± 4.84 years. Kaplan-Meier survival curves and Cox-proportional hazards analysis were used to analyze survival data. RESULTS: Multivariable analysis confirmed that ACHD was associated greater in-hospital death compared to ICM (HR = 0.54, P < 0.001) and NICM (HR = 0.46, P < 0.001). Notable factors associated with increased mortality were history of cerebrovascular disease (HR = 1.11, P = 0.026), prior history of malignancy (HR = 1.12, P = 0.006), pre-transplant biventricular support (HR = 1.12, P = 0.069), postoperative stroke (HR = 1.47, P < 0.001) and postoperative dialysis (HR = 1.71, P < 0.001). ACHD transplants had a longer donor heart ischemic time (P < 0.001) and trend towards more deaths from primary graft dysfunction (P = 0.07). In-hospital deaths were more likely with ACHD and use of mechanical support such as use of right ventricular assist device (HR = 2.20, P = 0.049), biventricular support (HR = 1.62, P < 0.001) and extracorporeal membrane oxygenation (HR = 2.36, P < 0.001). Conditional survival after censoring hospital deaths was significantly higher in ACHD (P < 0.001). CONCLUSION: Heart transplant in ACHD is associated with a higher post-operative mortality given anatomical complexity but a better long-term conditional survival. Normothermic donor heart perfusion may improve outcomes in the ACHD population by reducing the impact of longer ischemic times.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".