Effect of Ramipril on Urinary Protein Excretion in Maintenance Renal Transplant Patients Converted to Sirolimus
Bibliographic record
Abstract
This prospective, randomized, double-blind, placebo-controlled study evaluated the effects of ramipril on urinary protein excretion in renal transplant patients treated with sirolimus following conversion from a calcineurin inhibitor. Patients received ramipril or placebo for up to 6 weeks before conversion and 52 weeks thereafter. Doses were increased if patients developed proteinuria (urinary protein/creatinine ratio ≥0.5); losartan was given as rescue therapy for persistent proteinuria. The primary end point was time to losartan initiation. Of 295 patients randomized, 264 met the criteria for sirolimus conversion (ramipril, 138; placebo, 126). At 52 weeks, the cumulative rate of losartan initiation was significantly lower with ramipril (6.2%) versus placebo (23.2%) (p < 0.001). No significant differences were observed between ramipril and placebo for change in glomerular filtration rate from baseline (p = 0.148) or in the number of patients with biopsy-confirmed acute rejection (13 vs. 5, respectively; p = 0.073). One patient in the placebo group died due to cerebrovascular accident. Treatment-emergent adverse events were consistent with the known safety profile of sirolimus and were not potentiated by ramipril co-administration. Ramipril was effective in reducing the incidence of proteinuria for up to 1 year following conversion to sirolimus in maintenance renal 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".