Use of Cyclosporine Therapy in Steroid Resistant Nephrotic Syndrome (SRNS): A Review
Bibliographic record
Abstract
A chronic, progressive disorder Steroid Resistant Nephrotic Syndrome (SRNS) accounts for 10-20% of all children with Nephrotic Syndrome. It is a heterogeneous disorder comprised of persistent edema, proteinuria, hypoalbuminemia and hyperlipidemia. Treatment for steroid-resistant nephrotic syndrome (SRNS) is challenging and children who suffer from SRNS require aggressive treatment to achieve remission. Calcineurin inhibitors have been used more in an empirical manner than on the basis of clear rationale. It was in 1984 when cyclosporine was first considered for the treatment of steroid resistant nephrotic syndrome. Cyclosporin is a calcineurin inhibitor that suppresses immune response by downregulating the transcription of various cytokine genes. Till now many studies have been conducted to determine dosages, duration of therapy, side effects and advantages of cyclosporine. Treatment of SRNS remains a difficult challenge in pediatric nephrology. Treatment should be individualized according to the underlying histopathology, and clinical and environmental conditions of the children. There is an urgent need to distinguish as soon as possible those patients who may benefit from prolonged immunosuppressive treatment from those who will not benefit from such treatment and who will just suffer from its major side effects. The emerging evidence that the majority of genetic forms of SRNS should receive symptomatic treatment only, should also be clinically tested and studies baring its significance should be evaluated in the future.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".