Bibliographic record
Abstract
PURPOSE OF REVIEW: Chronic renal failure associated with long-term calcineurin inhibitor immunosuppression is a substantial clinical problem in the heart transplant population, compounded by difficulties in identifying patients likely to develop renal dysfunction. Several approaches, however, have been developed or are being investigated to preserve renal function in heart transplant patients. RECENT FINDINGS: Approaches to identify patients with an increased risk of developing renal dysfunction are being refined, and improved calcineurin inhibitor monitoring strategies are being investigated. Novel immunosuppressive regimens including mycophenolate mofetil and/or rapamycin that lack nephrotoxicity promise new therapeutic strategies with the efficacy of calcineurin inhibitor-based combinations. Temporary ('holiday') or permanent ('retirement') calcineurin inhibitor replacement with interleukin-2 receptor monoclonal antibodies has the potential to halt progressive renal dysfunction. Finally, emerging data on the renal protection afforded by angiotensin converting enzyme inhibitors and angiotensin II receptor blockers, either singly or in combination, provide another avenue of investigation. SUMMARY: Several strategies have demonstrated their potential to preserve or improve renal function in heart transplant patients in small studies. Large randomized controlled trials are necessary to determine the optimal strategies to prevent rejection while preserving renal function in the long-term management of heart transplant patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".