Proteinuria After Kidney Transplantation
Bibliographic record
Abstract
Proteinuria is a relatively frequent complication in both adults and children after kidney transplantation (40%-80%). It is usually mild and predominantly of tubular origin and is caused mainly by rejection, mTOR inhibitors, or hypertension; however, proteinuria could also be in the nephrotic range and of glomerular origin if caused by the recurrence of idiopathic FSGS or rejection. Proteinuria is a risk factor impacting graft and patient survival in adults and graft survival in children. Proteinuria should be assessed by protein/creatinine ratio regularly in pediatric kidney transplant recipients. In children with idiopathic FSGS, proteinuria should be assessed daily during the first 2-3 weeks post-transplant to enable prompt diagnosis of recurrence. The etiology of proteinuria should be identified (recurrence, rejection, mTOR-inhibitors, hypertension, etc.). If no apparent cause is found, a graft biopsy should be considered. Antiproteinuric therapy is primarily focused on treating the causes of the proteinuria, and this is usually done using Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARBs). The long-term follow-up goal should be normalization of proteinuria with a protein/creatinine ratio < 20 mg/mmol (200 mg/g). Because of the role elevated blood pressure may play in exacerbating proteinuria, antihypertensive medications should be used in those who are resistant to initial antiproteinuric therapy to achieve lower BP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".