Lupus Nephritis, Autoantibody Production and Kidney Outcomes in Males with Childhood-Onset Systemic Lupus Erythematosus
Bibliographic record
Abstract
Childhood-onset systemic lupus erythematosus (cSLE) only represents 20% of all SLE patients, and males with SLE only represent 10%. To study this rare SLE subset, males diagnosed with cSLE over a 30-year period were identified. Organ involvement, autoantibody production, hypocomplementemia, and kidney biopsy findings were compared to cSLE females. Outcomes were assessed using SLE Disease Activity Index scores, Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index, and Childhood Arthritis and Rheumatology Research Alliance definitions for nephritis responsiveness. Of 95 males and 545 females with cSLE, 62% and 57% developed nephritis, respectively. Median age of cSLE onset was 14 years in both genders. Among males, 80% of non-Hispanic whites, 64% of blacks, 59% of Hispanics, and 50% of Asians developed nephritis. The prevalence of pure and mixed class V membranous nephritis was 33%. Median follow-up was 3.2 years (range 0.1-18). Complete kidney responses were seen in 70% after a median 24 months; however, relapse rates were 46%. Kidney disease flares were 56% nephritic and 44% proteinuric. Males and females with cSLE present with comparable rates and nephritis class. While overall and kidney response rates are favorable, kidney disease relapses are common among males.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".