Impact of De Novo Everolimus-Based Immunosuppression on Incisional Complications in Heart Transplantation
Bibliographic record
Abstract
BACKGROUND: The mammalian target of rapamycin inhibitor sirolimus has been associated with an increased incidence of wound-healing complications after de novo heart transplantation. To evaluate the possibility of a similar association for everolimus, we performed a risk-factor analysis to compare the incidence of incision-related wound complications for everolimus with that of other adjunctive drugs. METHODS: Safety data from 1009 heart transplant recipients (n=214, receiving azathioprine; n=84, mycophenolate mofetil (MMF); n=711, everolimus) were reviewed in a post hoc analysis from three randomized, multicenter studies-B253 (n=634), A2403 (n=199), and A2411 (n=176)-in which de novo patients received fixed-dose or concentration-controlled everolimus (target trough, 3-8 ng/mL), azathioprine, or MMF with standard- or reduced-exposure cyclosporine A. Incisional complications were analyzed for incidence, type, and severity up to day 90 posttransplant. RESULTS: Incisional-complication events occurred in 25 (11.7%) azathioprine, six (7.2%) MMF, and 87 (12.3%) everolimus patients. Serious incisional complications were more frequent with everolimus (6.9%) compared with azathioprine (4.2%; P=0.197) or MMF (1.2%; P=0.051). In a univariate analysis, patient sex, body mass index (BMI), and diabetes were associated with incisional complications. Only BMI was significantly associated with incisional complications in the subsequent multivariate analysis, with the odds of an incisional-complication event increasing by 12.9% for every 1 kg/m increase in BMI (P<0.001). CONCLUSIONS: The incidence of incisional complications with everolimus was generally low, although numerically higher compared with MMF. Our analyses provided no strong evidence that everolimus is an independent risk factor for incisional complications. After de novo heart transplantation, patients with a high BMI are at higher risk of incision-related wound complications.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".