Anti-C1q antibodies in systemic lupus erythematosus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Anti-C1q has been associated with systemic lupus erythematosus (SLE) and lupus nephritis in previous studies. We studied anti-C1q specificity for SLE (vs rheumatic disease controls) and the association with SLE manifestations in an international multicenter study. METHODS: Information and blood samples were obtained in a cross-sectional study from patients with SLE (n = 308) and other rheumatologic diseases (n = 389) from 25 clinical sites (84% female, 68% Caucasian, 17% African descent, 8% Asian, 7% other). IgG anti-C1q against the collagen-like region was measured by ELISA. RESULTS: Prevalence of anti-C1q was 28% (86/308) in patients with SLE and 13% (49/389) in controls (OR = 2.7, 95% CI: 1.8-4, p < 0.001). Anti-C1q was associated with proteinuria (OR = 3.0, 95% CI: 1.7-5.1, p < 0.001), red cell casts (OR = 2.6, 95% CI: 1.2-5.4, p = 0.015), anti-dsDNA (OR = 3.4, 95% CI: 1.9-6.1, p < 0.001) and anti-Smith (OR = 2.8, 95% CI: 1.5-5.0, p = 0.01). Anti-C1q was independently associated with renal involvement after adjustment for demographics, ANA, anti-dsDNA and low complement (OR = 2.3, 95% CI: 1.3-4.2, p < 0.01). Simultaneously positive anti-C1q, anti-dsDNA and low complement was strongly associated with renal involvement (OR = 14.9, 95% CI: 5.8-38.4, p < 0.01). CONCLUSIONS: Anti-C1q was more common in patients with SLE and those of Asian race/ethnicity. We confirmed a significant association of anti-C1q with renal involvement, independent of demographics and other serologies. Anti-C1q in combination with anti-dsDNA and low complement was the strongest serological association with renal involvement. These data support the usefulness of anti-C1q in SLE, especially in lupus nephritis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.002 |
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 it