Neuropsychiatric events in systemic lupus erythematosus: attribution and clinical significance.
Bibliographic record
Abstract
OBJECTIVE: To describe the range and attribution of neuropsychiatric (NP) disease in an unselected cohort of patients with systemic lupus erythematosus (SLE) and to examine the association with cumulative organ damage, medication use, and quality of life. METHODS: One hundred eleven patients with SLE in a single referral center were studied. NP syndromes were defined using the American College of Rheumatology (ACR) nomenclature and case definitions. Overall disease activity was measured by the SLE Disease Activity Index (SLEDAI); cumulative organ damage was determined by the ACR/SLICC damage index; and quality of life by the SF-36. RESULTS: Patients' mean age was 44.7 years, 87% were female, and 92% were Caucasian. The mean (+/- SE) disease duration was 10.1 +/- 0.7 years. A total of 74 NP events were identified in 41 of 111 (37%) patients. Thirteen of the 19 ACR NP syndromes were identified and 2 or more NP manifestations occurred in 56% of patients. Central nervous system manifestations accounted for 92% of the events compared to involvement of the peripheral nervous system in 8%. Thirty-five (47%) of these events were attributed entirely to SLE, 30 (41%) were attributed exclusively to non-SLE factors, and in the remaining 9 events (12%) both SLE and non-SLE factors were felt to be contributory. Cumulative organ damage was higher in patients with NP disease, although this was not statistically significant and they were more likely to have received prednisone or immunosuppressive drugs (p < 0.05). Patients with NP disease reported more fatigue (p < 0.05) and had significantly lower scores on 7 of 8 subscales of the SF-36 (p < 0.05). These associations were found regardless of the attribution of NP disease. In contrast, the occurrence of renal disease in the same cohort of patients was not associated with lower SF-36 scores or fatigue. CONCLUSION: In patients with SLE, NP disease has diverse manifestations and can be attributed to lupus in roughly half of the cases. The occurrence of NP disease is associated with more frequent use of corticosteroids and immunosuppressive drugs. In contrast to other serious manifestations of SLE, such as renal disease, NP disease is associated with a significant reduction in quality of life.
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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 | 0.003 |
| 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 | 0.001 | 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".