Mycophenolate mofetil in the treatment of focal segmental glomerulosclerosis
Bibliographic record
Abstract
AIMS: Primary focal segmental glomerulosclerosis (FSGS) is a common cause of end-stage renal disease in both children and adults. Our current treatments are suboptimal, and a significant percentage of cases are resistant to current therapy. PATIENTS AND METHODS: We performed an open-label, 6-month trial of the new immunosuppressive agent mycophenolate mofetil (MMF) in 18 biopsy-proven patients resistant to a course of corticosteroids therapy. Seventy-five percent had also failed to respond to a cytotoxic agent and/or a calcineurin inhibitor. RESULTS: A substantial improvement in proteinuria was seen in 44% (8/18) of the patients by 6 months. This was sustained for up to 1 year post treatment in 50% (4/8) of this group. No patient had a complete remission. No deterioration in renal function was observed in any patient over the treatment period, but 3 progressed to chronic kidney failure during follow-up. Adverse effects were mild. Only 1 patient required a dose reduction due to an intercurrent infection. CONCLUSIONS: MMF appears safe to use in this group of patients and did lower proteinuria in 44% of this cohort resistant to other forms of treatment. Relapses were common, suggesting more prolonged or combination therapy may be required. More rigorous trials utilizing this medication should be considered to further assess the risk-benefit ratio of treatment with MMF in patients with FSGS.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".