UTILITY OF URINARY BIOMARKERS TO PREDICT LONG-TERM RENAL OUTCOMES IN LUPUS NEPHRITIS
Bibliographic record
Abstract
O048 / #626 Topic:AS15 - Lupus Nephritis-Clinical ABSTRACT CONCURRENT SESSION 08: RECENT ADVANCES IN LUPUS BIOMARKERS 23-05-2025 1:40 PM - 2:40 PM Background/Purpose Lupus nephritis (LN) affects up to 50% of patients with lupus, of whom 40% will experience a subsequent renal flare, and up to 20% will progress to end-stage renal disease. Repeat kidney biopsies (KB) performed 2 years after the last LN flare have been shown to predict subsequent renal flares and renal dysfunction. In this study, we assessed whether 5 urinary biomarkers (UB), including CD163, MCP-1, Adiponectin, sVCAM-1 and PF4 measured 2 years after a LN flare, predict long-term renal outcomes. Methods Patients who had a LN flare and stored urine 24±3 months after the LN flare were included in the study. The 5 UB levels were measured by ELISA 24±3 months after the LN flare. Examined renal outcomes: 1) Time to a subsequent LN flare (increase in proteinuria of at least 1000 mg/day if the baseline was <500 mg/day or doubling of proteinuria if the baseline was ≥500 mg/day, prompting a change in therapy) and 2) time to 30% decline in eGFR, after their 2-year urinary sample collection. Results 69 patients with LN were included. The median (IQR) follow-up time after their 2-year urinary sample collection was 129 (97.5-150) months. 50 patients achieved proteinuria of ≤700 mg at 2 years after the LN flare. This subcohort of patients had significantly lower UB levels 2 years after the LN flare compared to patients who persisted with proteinuria >700 mg (Figure 1). In this subcohort of patients, 27 (54%) experienced a subsequent LN flare with a median time to flare (IQR) of 3.5 (1.67-6.87) years, and 10 (20%) had a 30% decline in eGFR at a median time of 4.38 (3.73-5.33) years after their 2-year urinary sample collection. Elevated levels of MCP-1 (HR 1.13 (1.01-1.27), p=0.03) and CD163 (HR 1.48 (1.15-1.90), p=0.002) predicted a subsequent LN flare. While CD163 (HR 1.31 (1.10-1.57), p=0.002), Adiponectin (HR 1.53 (1.22-1.91), p=0.0002), sVCAM-1 (HR 1.11 (1.03-1.21), p=0.006), and PF4 (HR 1.14 (1.04-1.25), p=0.003) predicted a 30% decline in eGFR (Table 1). Figure 1. UB were significantly higher in patients who did not achieve an uPCR ≤700 mg (n=19) at 24±3 months after the LN flare as compared to those who did (n=50). Symbols represent the determination from a single individual, columns the median and the bars IQR. Table 1. Multivariable Cox Regression analysis. Predictors of adverse renal outcomes (Subcohort of patients who achieved a proteinuria of ≤700 mg at 24±3 months after the LN flare, N=50) Conclusions UB measured 2 years after an LN flare predicted long-term renal outcomes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".