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Record W4409327132 · doi:10.2215/cjn.0000000707

Proteinuria Trajectory and Disease Progression in Children and Adults with IgA Nephropathy/Vasculitis

2025· article· en· W4409327132 on OpenAlexaff
Dorey A. Glenn, A. Carver, Margaret Helmuth, Abigail R. Smith, Richard Lafayette, Prasanth Ravipati, Andrea L. Oliverio, Dana V. Rizk, Jan Novák, Francesca Lugani, Sharon Bartosh, Krzysztof Mucha, Krzysztof Kiryluk, Manish K. Saha, Cynthia C. Nast, Jean Hou, Laura Biederman, Nidia Messias, Avi Z. Rosenberg, Heather N. Reich, Pietro A. Canetta, Patrick H. Nachman, Carla Nester, Raed Bou-Matar, Shikha Wadhwani, Laura H. Mariani, Myda Khalid

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNephcure Foundation
KeywordsMedicineProteinuriaNephropathyInternal medicineRenal functionHazard ratioCohortProportional hazards modelKidney diseaseGastroenterologyKidneyEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Key Points Defining risk of kidney function loss in IgA nephropathy and IgA vasculitis with nephritis is important for patient counseling and risk-based enrollment of clinical trials. Proteinuria trajectory over 2 years can uniquely identify patients at risk of loss of kidney function or kidney failure. Children and adults with the highest levels of proteinuria had a higher risk of progressive kidney disease compared with those with intermediate levels. Background Identifying patients with IgA nephropathy at risk of disease progression is critical for clinical decision making, risk-based patient counseling, and optimal enrollment of clinical trials. Methods Patients with IgA nephropathy and IgA vasculitis with nephritis were enrolled in the Cure Glomerulonephropathy Network, a multicenter observational cohort study. Children and adults were analyzed separately in four cohorts: ( 1 ) full, ( 2 ) incident, ( 3 ) prevalent, and ( 4 ) histology. Groups were defined using latent class trajectory modeling using proteinuria measurements over 2 years. Linear mixed models were used to calculate predicted eGFR slope. In adults, Cox proportional hazard models were used to model time to kidney failure or 40% eGFR decline as a function of the proteinuria trajectory group. Results Of 919 patients with IgA nephropathy/IgA vasculitis with nephritis enrolled into the Cure Glomerulonephropathy Network, 368 adults and 234 children were included in the analysis. In the full adult cohort, group 1 had the lowest levels of proteinuria (interquartile range [IQR], 0.1–0.4 g/g), while groups 2 and 3 had intermediate and higher levels of proteinuria (IQR, 0.5–1.5 and IQR, 1.8–4.1 g/g), respectively. The average predicted time to eGFR <15 ml/min per 1.73 m 2 was >90, 16, and 8 years and >90, 67, and 11 years for proteinuria trajectory groups 1, 2, and 3 in the full adult and pediatric cohorts, respectively. In adults, adjusting for age, eGFR at enrollment, immunosuppression exposure, and hypertension, group 3 membership was associated with 3.13 (95% confidence interval [CI], 1.84 to 5.33), 1.98 (95% CI, 0.97 to 4.06), and 3.36 (95% CI, 1.59 to 7.13) times higher hazard of progressing to a composite outcome compared with group 2 membership in the full, prevalent, and histology cohorts, respectively, but not associated with progression in the incident cohort. Conclusions Proteinuria trajectory is a major predictor of disease progression in patients with IgA nephropathy.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.311
Teacher spread0.303 · 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

Citations14
Published2025
Admission routes1
Has abstractyes

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