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LUPUS NEPHRITIS: THE RESPONSE TO A PROTEIN OVERLOAD IS DIFFERENT IN GLOMERULAR VERSUS INTERSTITIAL SCLEROSIS AND MAY HELP TO IDENTIFY PATIENTS WITH POOR KIDNEY PROGNOSIS

2025· article· en· W4410513213 on OpenAlexvenueno aff
Ana Malvar, Valeria Albertón, Joaquin Maertinez, Ignacio Chidid, Andrea Flores, Alfredo Loor, Amelia Bernasconi, Ricardo Heguilén

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLupus nephritisKidneyNephritisGlomerulonephritisGlomerulosclerosisInternal medicineKidney diseasePathologyProteinuriaDisease

Abstract

fetched live from OpenAlex

PV128 / #610 Poster Topic: AS15 - Lupus Nephritis-Clinical Background/Purpose The kidney response to protein overload (PO) has major diagnostic and prognosis implications in the evaluation of progressive kidney diseases, a frequent finding in patients (Pts) with lupus nephritis (LN). The contribution of the tubulo-interstitial damage (more than the glomerular sclerosis) to the progression toward severe kidney failure is well known. Given that creatinine undergoes considerable tubular secretion, the assessment of sequential glomerular filtration rate (eGFR) after a PO could be used as a test detector of the tubular functional mass. The aim of this trial was to evaluate the kidney response to PO in LN pts with mainly glomerular (GS) vs tubulo-interstitial (TIS) sclerosis and their long follow-up. Time to achieve the composite event (CE), decrease of the eGFR ≥40% or needed of renal replacement therapy, was compared among both groups Methods All LN biopsies performed in Pts with pure Class III (n: 6) and Class IV (n: 20) LN from Jan 2011 up to Jun 2012 before withdrawing immunosuppression, were included. A total of 26 pts (14 with predominant GS and 12 with predominant TIS) underwent a protein load test to assess the functional kidney reserve (FKR). Test: After an overnight fast all the pts received an oral water load (20 ml/kg BW) and the urinary output was then replaced orally with equal volumes of water. In the morning, a 1.5 g/kg BW PO was provided. GFR was measured every 30 min. from 1 h before and up to 4 h following PO. The FKR index was calculated as the quotient between peak and baseline GFR. Variation of the eGFR by 30% from baseline was considered as a positive test or sufficient KFR meanwhile less than 30% was a negative one. Log-rank test was used to compare FKR test results. The Kaplan-Meier product-limit estimator was used and the survival curves, showing the response to the previously performed renal reserve study were compared using the log-rank test. P-values < 0.05 were accepted as statistically significant. All data is expressed as media± SD. Results Both groups (GS and TIS) were homogeneous about demographic characteristics at baseline. Pre PO media GFR (ml/min) was similar in GS and TIS (100.6 ± 11.4 and 99.5 ± 10.8; respectively). GFR rose after PO to a peak of 135 ±22.0 and to 125 ±27.5 ml/min in GS and TIS groups respectively. The FKR index was lower in TIS than in GS and CG (1.22 0.04 and 1.42 0.06 respectively (p-value < 0.05)). Time to the CE was 136.4 ±14 months in pts showing a positive test vs 89.9 ± 19 months in those with a negative test. (P-value < 0.05). Conclusions The results from this study suggest that in LN patients the presence of tubulo-interstitial damage drastically reduces the renal response to a protein overload in contrast with the almost normal response obtained in patients with predominant glomerular involvement. This lack of response to a protein overload is related to poor long-term evolution. The assessment of the functional kidney reserve may help to balance the decision whether to start/continue /enhance immunosuppression in those patients with kidney sclerosis.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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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