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Record W4414311529 · doi:10.1016/j.xkme.2025.101104

Association Between Relapse and Long-Term Kidney Outcomes in IgA Nephropathy

2025· article· en· W4414311529 on OpenAlexfundno aff
Xue Shen, Pei Chen, Miao Hui, Jingyi Li, Wanyin Hou, Hongyu Yang, Li Yang, Lijun Liu, Sufang Shi, Jicheng Lv, Hong Zhang

Bibliographic record

VenueKidney Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsnot available
FundersPeking UniversityNational Key Research and Development Program of ChinaChinook TherapeuticsChinese Academy of Medical Sciences Initiative for Innovative MedicineNational Natural Science Foundation of ChinaPeking University First Hospital
KeywordsProteinuriaNephropathyKidneyKidney diseaseRenal function

Abstract

fetched live from OpenAlex

Rationale & Objective: Relapse in IgA nephropathy (IgAN) remains under-researched. This study investigates the incidence of IgAN relapse, its association with adverse outcomes, and its risk factors within a prospective cohort. Study Design: Prospective cohort study. Setting & Participants: The study included 1,069 patients with IgAN who achieved remission following treatment. Predictor: Relapse or not after remission of IgAN. Outcomes: , dialysis, or kidney transplantation) or a 50% decline in eGFR. Analytical Approach: We assessed relapse incidence, its correlation with kidney endpoint events, and identified clinicopathological predictors of relapse using Cox regression analysis. Least Absolute Shrinkage and Selection Operator Cox regression was performed to screen predictive variables to predict relapse. Results: /year). Patients with corticosteroid-induced remission had a higher likelihood of relapse within 3 years. Controlling 24-hour urinary protein at remission to below 0.3 g/d was associated with a significantly improved relapse-free rate. Limitations: Single-center study; no standardized definition for IgAN remission and relapse. Conclusions: Relapse is prevalent in IgAN and is associated with an increased rate of kidney endpoint events and accelerated eGFR decline. Predictors of relapse encompass various clinicopathological indicators and medications, with stricter control of proteinuria at remission being crucial for reducing relapse rates.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation 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 score0.093
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.298
Teacher spread0.286 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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