Impact of baseline proteinuria level on long-term outcomes in lupus nephritis
Bibliographic record
Abstract
OBJECTIVES: Proteinuria is a marker of lupus nephritis (LN) activity and damage. We aimed to explore the impact of baseline proteinuria level on long-term outcomes. METHODS: We included 249 patients diagnosed with their first biopsy-proven LN. We divided patients based on baseline proteinuria into low-level (≤1 g/day, group 1; 62 patients), moderate-level (>1 and <3 g/day, group 2; 90 patients) and high-level proteinuria (≥3 g/day, group 3; 97 patients). Outcomes included complete proteinuria recovery (CPR) at 1 year, an adverse composite outcome (ESKD, a sustained ≥40% decline in eGFR, or death) and LN flares. Cox proportional hazard models were used to examine the association between baseline characteristics and long-term outcomes. RESULTS: At baseline, the median [IQR] age was 33.2 [26.4, 42.4] years; median proteinuria level was 2.2 [1.0, 3.8] g/day. A total of 177 (71%) patients had proliferative lesions on biopsy; 59.7% in group 1, 78.9% in group 2 and 71.4% in group 3. The rate of achievement of CPR at 1 year was highest for group 1 and lowest for group 3. For long-term outcomes (median follow-up 8.4 years), the frequency of the adverse composite outcome was 27.4%, 26.7% and 48.5% in groups 1, 2 and 3, respectively; P = 0.003. The corresponding frequency of flares was 27.4%, 38.2% and 61.9%, respectively; P < 0.001. In the multivariable model for factors associated with long-term outcomes, there was no significant difference between groups 1 and 2; group 3 was associated with the worst prognosis. CONCLUSIONS: Low-level proteinuria is commonly associated with proliferative LN and adverse long-term 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".