RENAL BIOPSY DATA IN LUPUS PATIENTS WITH LOW PROTEINURIA
Bibliographic record
Abstract
PV120 / #816 Poster Topic: AS15 - Lupus Nephritis-Clinical Background/Purpose Systemic lupus is an extremely protean, chronic disease, evolving in flares, the severity of which varies depending on the severity of the affected organs. Renal involvement during lupus is a major prognostic factor. The objective of our study is to evaluate histological renal involvement in lupus patients with proteinuria < 1.2 g/24 and to determine the impact on the therapeutic project. Methods This is a 2-year retrospective study from January 2023 to January 2025 including lupus patients with proteinuria between 0.7 and 1.2 g/24h who underwent a renal biopsy. We excluded those with renal failure. Results We gathered 23 patients with an average age of 28 years +/- 22 years, the female gender predominates in our study, making up all the patients gathered. The average proteinuria rate was 1g/24h. The indication for renal biopsy was proteinuria in 86% of cases, as well as proteinuria associated with hematuria in 14% of cases. Renal biopsy puncture showed class III lupus nephropathy in 17% of cases, class IV or IV+V in 40% of cases and class V found in 43% of cases The use of immunosuppressants and full-dose corticosteroid therapy was imperatively instituted in 83% of cases. As a result, even low proteinuria can reveal advanced class lupus nephropathy, which underlines the absence of anatomoclinical correlation and joins the new KDIGO 2024 recommendations, a renal biopsy puncture should be considered in the event of proteinuria > or equal to 500 mg/day and/or active urinary sediment. Conclusions As a conclusion, according to our study, a biopsy puncture is necessary in the event of even minimal urinary sediment abnormalities, given the absence of anatomoclinical correlation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".