A pilot study of reduced dose cyclosporine and corticosteroids to reduce new onset diabetes mellitus and acute rejection in kidney transplant recipients
Bibliographic record
Abstract
BACKGROUND: New onset diabetes mellitus (NODM) and acute rejection (AR) are important causes of morbidity and risk factors for allograft failure after kidney transplantation. METHODS: In this multi-center, open label, single-arm pilot study, 49 adult (≥18 years of age), low immunologic risk, non-diabetic recipients of a first deceased or living donor kidney transplant received early steroid reduction to 5 mg/day combined with Thymoglobulin® (Genzyme Transplant, Cambridge, MA, USA) induction, low dose cyclosporine (2-hour post-dose (C2) target of 600 to 800 ng/ml) and mycophenolic acid (MPA) therapy. RESULTS: Six months after transplantation, two patients (4%) developed NODM and one patient (2%) developed AR. Four patients had impaired fasting glucose tolerance based on 75-g oral glucose tolerance testing (OGTT). There was one patient death. There were no episodes of cytomegalovirus (CMV) infection or BK virus nephritis. In contrast, in a historical cohort of n = 27 patients treated with Thymoglobulin induction, and conventional doses of cyclosporine and corticosteroids, the incidence of NODM and AR was 18% and 15%. CONCLUSIONS: The pilot study results suggest that Thymoglobulin induction combined with early steroid reduction, reduced cyclosporine exposure and MPA, may reduce the incidence of both NODM and AR in low immunological risk patients. A future controlled study enriched for patients at high risk for NODM is under consideration. TRIAL REGISTRATION: ClinicalTrials.gov: http://NCT00706680.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".