IPNA clinical practice recommendations for the diagnosis and management of children with steroid-sensitive nephrotic syndrome
Bibliographic record
Abstract
Idiopathic nephrotic syndrome is the most frequent pediatric glomerular disease, affecting from 1.15 to 16.9 per 100,000 children per year globally. It is characterized by massive proteinuria, hypoalbuminemia, and/or concomitant edema. Approximately 85-90% of patients attain complete remission of proteinuria within 4-6 weeks of treatment with glucocorticoids, and therefore, have steroid-sensitive nephrotic syndrome (SSNS). Among those patients who are steroid sensitive, 70-80% will have at least one relapse during follow-up, and up to 50% of these patients will experience frequent relapses or become dependent on glucocorticoids to maintain remission. The dose and duration of steroid treatment to prolong time between relapses remains a subject of much debate, and patients continue to experience a high prevalence of steroid-related morbidity. Various steroid-sparing immunosuppressive drugs have been used in clinical practice; however, there is marked practice variation in the selection of these drugs and timing of their introduction during the course of the disease. Therefore, international evidence-based clinical practice recommendations (CPRs) are needed to guide clinical practice and reduce practice variation. The International Pediatric Nephrology Association (IPNA) convened a team of experts including pediatric nephrologists, an adult nephrologist, and a patient representative to develop comprehensive CPRs on the diagnosis and management of SSNS in children. After performing a systematic literature review on 12 clinically relevant PICO (Patient or Population covered, Intervention, Comparator, Outcome) questions, recommendations were formulated and formally graded at several virtual consensus meetings. New definitions for treatment outcomes to help guide change of therapy and recommendations for important research questions are given.
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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 | 0.017 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".