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Record W4408360378 · doi:10.1016/j.ekir.2025.03.008

Corticosteroid Effects in IgA Nephropathy by Baseline Proteinuria and Estimated GFR

2025· article· en· W4408360378 on OpenAlexafffund
Dana Kim, Brendon L. Neuen, Jicheng Lv, Michelle Hladunewich, Vivekanand Jha, Lai Seong Hooi, Helen Monaghan, Robert A. Fletcher, Laurent Billot, Vlado Perkovic, Hong Zhang, Muh Geot Wong

Bibliographic record

VenueKidney International Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsSunnybrook Health Science Centre
FundersChinese Academy of Medical Sciences Initiative for Innovative MedicineNational Key Research and Development Program of China Stem Cell and Translational ResearchMedical Research CouncilNational Key Research and Development Program of ChinaPeking UniversityCanadian Institutes of Health ResearchChinese Academy of Medical SciencesPeking University First HospitalChina National Funds for Distinguished Young ScientistsNational Health and Medical Research CouncilPfizer
KeywordsMedicineProteinuriaNephropathyCorticosteroidInternal medicineImmunologyEndocrinologyKidney

Abstract

fetched live from OpenAlex

Introduction Higher proteinuria and lower estimated glomerular filtration rate (eGFR) are predictors of kidney failure in IgA nephropathy (IgAN); however, it is uncertain whether these markers modify response to corticosteroids. This post hoc analysis of the TESTING trial assessed the effects of methylprednisolone on kidney and safety outcomes by baseline proteinuria and eGFR. Methods A total of 503 participants with IgAN and proteinuria ≥ 1 g/d were randomized to oral methylprednisolone (full-dose 0.6–0.8 mg/kg/d or reduced-dose 0.4 mg/kg/d) versus placebo. Participants were categorized according to baseline proteinuria (1–< 1.5, 1.5–< 3, ≥ 3 g/d) and eGFR (20–< 30, 30–< 45, 45–< 60, 60–120 ml/min per 1.73 m 2 ). Results Over a mean follow-up of 4.2 years, methylprednisolone lowered the risk of the primary outcome (≥ 40% decline in eGFR, kidney failure, or death because of kidney disease) by 47% (hazard ratio: 0.53, 95% confidence interval [CI]: 0.39–0.72), with consistent effects regardless of baseline proteinuria ( P -interaction = 0.53) or eGFR ( P -interaction = 0.68). Similarly, methylprednisolone improved the decline in total eGFR slope and reduced proteinuria, regardless of baseline proteinuria or eGFR (all P -interaction > 0.10). The number of serious adverse events (SAEs) was higher with methylprednisolone than with placebo across all proteinuria and eGFR levels. Absolute benefits and harms varied by eGFR, such that for those with eGFR < 30 ml/min per 1.73 m 2 , absolute risk of SAEs may outweigh potential advantages. However, this subgroup was small, predominantly received full-dose methylprednisolone, and was older than those with eGFR ≥ 30 ml/min per 1.73 m 2 . Conclusion Methylprednisolone improves kidney outcomes in IgAN at high risk of progression, irrespective of proteinuria or eGFR, although the risk-benefit balance may be less favorable in those with advanced disease plus other risk factors for corticosteroid-related toxicities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.006
GPT teacher head0.279
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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