Comparative Analysis of Damage Accrual in Lupus Nephritis Stratified by Biological Sex
Bibliographic record
Abstract
OBJECTIVE: Several studies in systemic lupus erythematosus (SLE) have suggested that male individuals may experience a higher risk of damage compared to female individuals. However, this has not been adequately explored in cohorts focused specifically on lupus nephritis (LN). We aimed to investigate sex-based differences in the accrual of both extrarenal and renal damage in a cohort of patients with LN. METHODS: This retrospective study included patients with SLE from an observational cohort who developed LN at or after clinic entry. Outcomes of extrarenal and renal damage were assessed using the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI) and kidney function measures. Statistical analyses included Fine-Gray subdistribution hazard models and Kaplan-Meier survival analysis. RESULTS: The cohort included 460 patients, with a predominance of female individuals (83.5%) and a median age of 33 years. Over a median follow-up of 8.6 years, 45.3% of patients accrued extrarenal damage, defined as an increase in nonrenal SDI by ≥ 1, whereas 32.2% experienced renal damage, defined as a composite of either a sustained ≥ 30% decline in estimated glomerular filtration rate or progression to end-stage kidney disease. No significant differences in the accrual of damage were observed between male and female individuals, and the time to outcomes was not statistically different between both sexes. Multivariable analysis revealed that male sex was not associated with higher damage accrual, either extrarenal (hazard ratio [HR] 1.13, 95% CI 0.76-1.70) or renal (HR 1.26, 95% CI 0.67-2.36). CONCLUSION: Extrarenal and renal damage accrual are frequent in patients with LN and do not appear to be higher in male individuals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".