Therapeutic strategies and outcomes in neuropsychiatric systemic lupus erythematosus: an international multicentre retrospective study
Bibliographic record
Abstract
OBJECTIVES: The management of neuropsychiatric systemic lupus erythematosus (NPSLE) poses considerable challenges due to limited clinical trials. Therapeutic decisions are customized based on suspected pathogenic mechanisms and symptoms severity. This study aimed to investigate therapeutic strategies and disease outcome for patients with NPSLE experiencing their first neuropsychiatric (NP) manifestation. METHODS: This retrospective cohort study defined NP events according to the American College of Rheumatology case definition, categorizing them into three clusters: central/diffuse, central/focal and peripheral. Clinical judgment and a validated attribution algorithm were used for NP event attribution. Data included demographic variables, SLE disease activity index, cumulative organ damage, and NP manifestation treatments. The clinical outcome of all NP events was determined by a physician seven-point Likert scale. Predictors of clinical improvement/resolution were investigated in a multivariable logistic regression analysis. RESULTS: The analysis included 350 events. Immunosuppressants and corticosteroids were more frequently initiated/escalated for SLE-attributed central diffuse or focal NP manifestations. At 12 months of follow-up, 64% of patients showed a clinical improvement in NP manifestations. Focal central events and SLE-attributed manifestations correlated with higher rates of clinical improvement. Patients with NP manifestations attributed to SLE according to clinical judgment and treated with immunosuppressants had a significantly higher probability of achieving clinical response (OR 2.55, 95%CI 1.06-6.41, P = 0.04). Age at diagnosis and focal central events emerged as additional response predictors. CONCLUSION: NP manifestations attributed to SLE by clinical judgment and treated with immunosuppressants demonstrated improved 12-month outcomes. This underscores the importance of accurate attribution and timely diagnosis of NPSLE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".