Cognitive Dysfunction in Patients with Systemic Lupus Erythematosus: A Controlled Study
Bibliographic record
Abstract
OBJECTIVE: To determine the extent to which cognitive dysfunction (CD) observed in patients with systemic lupus erythematosus (SLE) exceeds that seen in a matched control group of patients with rheumatoid arthritis (RA), and to estimate the prevalence of CD in SLE in a community-based sample. METHODS: A random subsample of 31 patients with SLE was compared to patients with RA matched by age, sex, and race and derived from the same patient population. Cognitive function was assessed by the Automated Neuropsychological Assessment Metrics (ANAM). The primary outcome was the total throughput score (number of correct responses divided by the time taken for those responses averaged over all subtests), adjusted for premorbid intelligence, neuromuscular efficiency, disease activity, damage, depression, fatigue, and health-related quality of life. RESULTS: There were no statistically significant differences in mean throughput scores between patients in the SLE and RA groups in any subtest of the ANAM or in the total throughput score. The frequency of CD, defined as either total scores > 1.5 SD below the mean of the RA population, or 4 or more ANAM subtests each > 1.5 SD below the RA mean, was similar in patients with SLE and in RA controls. CONCLUSION: We found no differences in cognitive function between patients with SLE and RA, suggesting that the CD found in some patients with SLE may represent the consequences of a chronic and/or inflammatory disease rather than SLE-related central nervous system damage.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".