Sirolimus Immunoprophylaxis and Renal Histological Changes in Long-Term Cardiac Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The effects of sirolimus (SIR), as a substitution for calcineurin inhibitor (CNI) immunoprophylaxis, on renal function in very-long-term cardiac transplant recipients have been a matter of controversy. OBJECTIVE: To assess the impacts of SIR as a substitution for CNI on renal function up to 24 months in long-term cardiac recipients as well as the renal histological changes in patients with suspected CNI-induced nephrotoxicity. METHODS: A total of 23 cardiac transplant recipients aged 57.7 ± 11.2 years, 91 months post-cardiac transplantation were recruited; 15 patients were randomized to CNI-free immune suppression with SIR, and 8 patients were allocated to continue their CNI regimens. Serum creatinine and calculated serum creatinine clearance were measured at prespecified time points up to 24 months. Renal structure and function were assessed by renal biopsies, renal ultrasound, and magnetic resonance imaging at baseline. RESULTS: There were no significant changes in creatinine clearance during the course of the study in patients treated with SIR. However, SIR-treated patients exhibited a significant decrease in 24-hours and nighttime systolic and diastolic blood pressures. Typical findings of significant hypertensive renal disease were detected in 9 of the 11 (82%) patients. Features of chronic CNI toxicity were detected in 6 (55%) patients. CONCLUSIONS: There is a very high rate of hypertensive renal disease concomitantly with some degree of CNI toxicity in long-term cardiac transplant recipients with renal dysfunction. This very high rate of hypertension-related disease may limit the impact of SIR on improving renal function long term following cardiac transplantation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".