A pilot protocol of a calcineurin‐inhibitor free regimen for kidney transplant recipients of marginal donor kidneys or with delayed graft function
Bibliographic record
Abstract
UNLABELLED: The worsening shortage of cadaver donor kidneys has prompted use of expanded or marginal donor kidneys (MDK), i.e. older age or donor history of hypertension or diabetes. MDK may be especially susceptible to calcineurin-inhibitor (CI) mediated vasoconstriction and nephrotoxicity. Similarly, early use of CI in patients with delayed graft function may prolong ischaemic injury. We developed a CI-free protocol of antibody induction, sirolimus, mycophenolate mofetil, and prednisone in recipients with MDK or DGF. METHODS: Adult renal transplant recipients who received MDK or had DGF were treated with a CI-free protocol consisting of antibody induction (basiliximab or thymoglobulin), sirolimus, mycophenolate mofetil, and prednisone. Serial biopsies were performed for persistent DGF. Patients were followed prospectively with the primary endpoints being patient and graft survival, biopsy-proven acute rejection, and sirolimus-related toxicity. RESULTS: Nineteen recipients were treated. Mean follow-up was 294 days. Actuarial 6- and 12-month patient survival was 100% and 100% and graft survival was 93% and 93%, respectively. The only graft loss was due to primary non-function (PNF). The incidence of AR was 16%. Mean serum creatinine at last follow-up was 1.6 mg/dL. Sirolimus-related toxicity included lymphocele (1), wound infection (2), thrombocytopenia (1). and interstitial pneumonitis (1). CONCLUSION: A CI-free protocol with antibody induction and sirolimus results in low rates of AR and PNF and excellent early patient and graft survival in patients with MDK and DGF. CI-free protocols may allow expansion of the kidney donor pool by encouraging utilization of MDK at high risk for DGF or CI-mediated nephrotoxicity.
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 | 0.000 |
| 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) | 0.000 | 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".