An update on corticosteroid treatment for IgA nephropathy
Bibliographic record
Abstract
PURPOSE OF REVIEW: The use of corticosteroids to treat IgA nephropathy (IgAN) has been limited by many controversies related to uncertain benefit and safety concerns. Recent trials have tried to address these limitations. RECENT FINDINGS: After being paused because of an excess of adverse events in the full-dose steroid arm, the TESTING trial compared a reduced dose of methylprednisolone to placebo in patients with IgAN after optimization of supportive therapy. Steroid treatment was associated with a significant reduction in the risk of a 40% decline in estimated glomerular filtration rate (eGFR), kidney failure and kidney death as well as a sustained decrease in proteinuria compared with placebo. Serious adverse events were more frequent with the full dose regimen but less common in the reduced dose regimen. A phase III trial evaluating a new formulation of targeted-release budesonide showed a significant reduction in short-term proteinuria and has resulted in accelerated FDA approval for use in the United States. In a subgroup analysis of DAPA-CKD trial, sodium-glucose transport protein 2 inhibitors reduced the risk of kidney function decline in patients who have completed or are not eligible for immunosuppression. SUMMARY: Both reduced-dose corticosteroids and targeted-release budesonide are new therapeutic options that can be used in patients with high-risk disease. More novel-targeted therapies with a better safety profile are currently under investigations.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".