Everolimus is associated with a reduced incidence of cytomegalovirus infection following <i>de novo</i> cardiac transplantation
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) causes several complications following cardiac transplantation including cardiac allograft vasculopathy. Previous studies suggested that immunosuppressive treatment based on everolimus might reduce CMV infection. Aiming to better characterize the action of everolimus on CMV and its interplay with patient/recipient serology and anti-CMV prophylaxis, we analyzed data from 3 large randomized studies comparing various everolimus regimens with azathioprine (AZA)- and mycophenolate mofetil (MMF)-based regimens. METHODS: CMV data were analyzed from 1009 patients in 3 trials of de novo cardiac transplant recipients who were randomized to everolimus 1.5 mg/day, everolimus 3 mg/day, or AZA 1-3 mg/kg/day, plus standard-dose (SD) cyclosporine (CsA; study B253, n = 634); everolimus 1.5 mg/day plus SD- or reduced-dose (RD)-CsA (study A2403, n = 199); and everolimus 1.5 mg/day plus RD-CsA or MMF plus SD-CsA (study A2411, n = 176). RESULTS: In study B253, patients allocated to everolimus experienced almost a 70% reduction in odds of experiencing CMV infection compared with AZA (P < 0.001). In study A2403, CMV infection was low in both everolimus arms, irrespective of CsA dosing, and in study A2411, patients allocated to everolimus experienced an 80% reduction in odds of experiencing CMV infection, compared with MMF (P < 0.001). CMV syndrome/disease was rare and less frequent in everolimus-treated patients. Subgroup analyses showed that the benefit everolimus provides, in terms of CMV events, is retained in CMV-naïve recipients and is independent of anti-CMV prophylaxis or preemptive approaches. CONCLUSIONS: Everolimus is associated with a lower incidence of CMV infection compared with AZA and MMF, which combined with its immunosuppressive efficacy and antiproliferative effects may positively impact long-term outcomes.
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 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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".