Primary Sjogren’s syndrome: cognitive symptoms, mood, and cognitive performance
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationships between self-reported cognitive abilities, psychological symptoms and neuropsychological outcomes in PSS. METHODS: Patients with Primary Sjogren's syndrome (PSS) and healthy controls completed a comprehensive neuropsychometric battery and questionnaires: the Centers for Epidemiological Scale-Depression, the Profile of Fatigue-mental domain (Prof-M) for cognitive symptoms, Fatigue Severity Scale, and the Short-Form McGill Pain Questionnaire. RESULTS: Female patients with PSS (N = 39) were similar to controls (N = 17) in estimated premorbid intellectual function, age and education. Depression (P = 0.002), cognitive symptoms (P = 0.001), fatigue (P = 0.000003), and pain (P = 0.024) scores were greater in the patient group. Patients with PSS demonstrated inferior performance relative to controls in psychomotor processing (P = 0.027) and verbal reasoning (P = 0.007). Patients with PSS with and without depression had similar performance on multiple tests, but depressed patients had significantly lower scores for executive function (P = 0.041). Cognitive symptoms correlated with verbal memory (P = 0.048), whereas pain correlated with executive function measures (Stroop, P = 0.017) and working memory (Trails B, P = 0.036). In the regression model, depression and verbal memory were independent predictors that accounted for 61% of the variance in cognitive symptoms. CONCLUSION: The Prof-M is a simple self-report measure which could be useful in screening PSS subjects who may benefit from detailed psychometric evaluation. Our results are consistent with the hypothesis that depression and verbal memory impairment are overlapping but independent aspects of neural involvement in PSS. While pain and depression are significant confounders of cognitive function in PSS, this study suggests that impaired verbal reasoning ability in PSS is not attributable to pain or depression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".