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Record W4410715691 · doi:10.3899/jrheum.2025-0390.o041

PREDICTIVE VALUE OF CHRONIC HISTOLOGIC CHANGES IN LUPUS NEPHRITIS

2025· article· en· W4410715691 on OpenAlexvenueno aff
María C. Cuéllar‐Gutiérrez, Jaime Flores‐Gouyonnet, Gabriel Figueroa‐Parra, Marta Casal Moura, Fernando C. Fervenza, Cynthia S. Crowson, Alí Duarte‐García, Sanjeev Sethi

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLupus nephritisPredictive valueValue (mathematics)Systemic lupus erythematosusNephritisDermatologyPathologyInternal medicineDisease

Abstract

fetched live from OpenAlex

O041 / #709 Topic:AS15 - Lupus Nephritis-Clinical ABSTRACT CONCURRENT SESSION 06: LUPUS NEPHRITIS – CLINICAL OUTCOMES, PREDICTION AND THERAPY 23-05-2025 1:40 PM - 2:40 PM Background/Purpose The Mayo Clinic Chronicity Score (MCCS) is a tool to assess the chronicity of renal histology in glomerulopathies. This tool includes arteriosclerosis (AE), a chronic vascular lesion, and has not been evaluated in lupus nephritis (LN). Our objective was to evaluate the predictive value of the individual components of the International Society of Nephrology/Renal Pathology Society and MCCS in LN. Methods LN patients from Mayo Clinic between 1992 and 2023 were included. The earliest kidney biopsy was index date. Follow-up was until July 2023, death or loss follow-up. Biopsy reports were reviewed by a nephropathologist and chronic lesions reclassified (glomerulosclerosis [GS], interstitial fibrosis [IF], tubular atrophy [TA], arteriosclerosis [AE], and fibrous crescents [FC]). The outcomes were proteinuria <500 mg/day and complete renal response (CRR) within 1-year, end-stage kidney disease (ESKD), and death. We used stratified multivariable proportional hazards regression adjusted for sex and age. P-values <0.05 were statistically significant. Results We included 307 patients (median age, 34 years; 75% female; median follow-up, 11 years). The majority had class III, IV. FC were in 4.9%, AE in 12%. Table shows hazard ratios of proteinuria<500 mg/day, CRR, ESRD, and death for different variables of interest. At one year, 47.5% had proteinuria <500 mg/day and 43.4% CRR. Those with grade 2-3 of GS (HR 0.21 [0.09, 0.48]) and grade 2-3 IFTA (HR 0.14 [0.05, 0.39]) were less likely to achieve proteinuria <500 mg/day. Grade 2-3 of GS (HR 0.19 [0.08, 0.48]) and grade 2-3 IFTA (HR 0.16 [0.06, 0.44]) were also less likely to achieve CRR. (Figure 1) shows increasing grades of GS is associated with a lower chance of CRR. Similarly, AE (HR 0.44 [0.21, 0.91], for proteinuria <500 mg/day, HR 0.37 [0.16, 0.84], for CRR) was associated with a reduced likelihood of achieving the outcomes. During follow-up, 33 patients died, and 60 developed ESKD. No variables were associated with mortality. Grade 2-3 GS (HR 9.28 [4.91, 17.54], grade 2-3 IFTA (HR 20.10 [10.08, 40.08]), and the presence of AE (HR 3.56 [1.87, 6.78]) were associated with an increased ESKD. (Figure 2) shows increasing grades of GS is associated with a greater chance of ESKD. Table. Hazard ratios of proteinuria <500 mg/day, CRR, ESKD, and death for variables. Figure 1: Kaplan Meier curve for complete renal response (CRR) for glomerulosclerosis (GS) score. Black line: GS grade 0, red: GS grade 1, green: GS grades 2-3. Increasing GS is associated with a lower chance of CRR. Figure 2: Kaplan Meier curve for end stage kidney disease (ESKD) for glomerulosclerosis (GS) score. Black line: GS grade 0, red: GS grade 1, green: GS grades 2-3. Increasing GS is associated with greater hazard of ESKD Conclusions GS, IFTA, AE are independently associated with outcomes in LN. FC is rare finding. The MCCS included all the chronic histologic elements associated with outcomes in LN.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.294
Teacher spread0.279 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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