Autoantibodies and neuropsychiatric events at the time of systemic lupus erythematosus diagnosis: Results from an international inception cohort study
Bibliographic record
Abstract
OBJECTIVE: To examine, in an inception cohort of systemic lupus erythematosus (SLE) patients, the association between neuropsychiatric (NP) events and anti-ribosomal P (anti-P), antiphospholipid (lupus anticoagulant [LAC], anticardiolipin), anti-beta2-glycoprotein I, and anti-NR2 glutamate receptor antibodies. METHODS: NP events were identified using the American College of Rheumatology case definitions and clustered into central/peripheral and diffuse/focal events. Attribution of NP events to SLE was determined using decision rules of differing stringency. Autoantibodies were measured without knowledge of NP events or their attribution. RESULTS: Four hundred twelve patients were studied (87.4% female; mean +/- SD age 34.9 +/- 13.5 years, mean +/- SD disease duration 5.0 +/- 4.2 months). There were 214 NP events in 133 patients (32.3%). The proportion of NP events attributed to SLE varied from 15% to 36%. There was no association between autoantibodies and NP events overall. However, the frequency of anti-P antibodies in patients with central NP events attributed to SLE was 4 of 20 (20%), versus 3 of 107 (2.8%) in patients with other NP events and 24 of 279 (8.6%) in those with no NP events (P = 0.04). Among patients with diffuse NP events, 3 of 11 had anti-P antibodies (27%), compared with 4 of 111 patients with other NP events (3.6%) and 24 of 279 of those with no NP events (8.6%) (P = 0.02). Specific clinical-serologic associations were found between anti-P and psychosis attributed to SLE (P = 0.02) and between LAC and cerebrovascular disease attributed to SLE (P = 0.038). There was no significant association between other autoantibodies and NP events. CONCLUSION: Clinically distinct NP events attributed to SLE and occurring around the time of diagnosis were found to be associated with anti-P antibodies and LAC. This suggests that there are different autoimmune pathogenetic mechanisms, although low sensitivity limits the clinical application of testing for these antibodies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".