Recent Advances in Mammalian Target of Rapamycin Inhibitor Use in Heart and Lung Transplantation
Bibliographic record
Abstract
In Brief The mammalian target of rapamycin (mTOR) inhibitors sirolimus and everolimus are increasingly used in cardiothoracic transplantation. Several recent clinical trials have demonstrated their efficacy in combination with reduced cyclosporine dosing in de novo heart transplant recipients, in particular with everolimus. A number of other studies have demonstrated their efficacy for improving renal function and reducing calcineurin inhibitor use, attenuating cardiac allograft vasculopathy progression and reducing cytomegalovirus infections in maintenance heart transplant populations. A growing body of literature, including a small number of clinical trials, now describes the use mTOR inhibitors in lung transplant recipients. The benefits in this population include improved lung and renal function in limited studies. Considerably less evidence is available in pediatric heart transplantation, though similar indications in the maintenance therapy population have been described. The benefits of mTOR inhibitors must be weighed against the increased risk of adverse events and drug intolerance compared with other primary immunosuppressants, and discontinuation rates are particularly high in lung transplant recipients. The risks of surgical wound healing complications in transplant recipients receiving mTOR inhibitors previously or actively supported by mechanical circulatory support devices remains poorly described in the current literature. The current role and recent evidence for mTOR inhibitor use in heart and lung transplantation is examined in this review. The overview summarizes the growing body of data regarding the use of mammalian target of rapamycin inhibitors in cardiothoracic transplantation. The beneficial effects on acute rejection, renal function and cardiac vasculopathy should be balanced against the adverse events and the increasing complexity of the recipients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".