Cognitive dysfunction in Sjögren’s syndrome using the Montreal Cognitive Assessment Questionnaire and the Automated Neuropsychological Assessment Metrics: A cross‐sectional study
Bibliographic record
Abstract
AIM: To describe the prevalence of cognitive impairment and the most affected cognitive domains, employing the Montreal Cognitive Assessment (MoCA) and the Automated Neuropsychological Assessment Metrics (ANAM) of a Latin American primary Sjögren's syndrome (pSS) cohort, and compare these patients to secondary Sjögren's syndrome (sSS) subjects and controls. METHODS: This was a comparative cross-sectional study of patients with a diagnosis of pSS who fulfilled the American-European Consensus Group 2002 criteria and/or American College of Rheumatology/European League Against Rheumatism 2016 criteria; clinical information was evaluated prior to cognitive evaluation, which consisted of a single session in which the MoCA and ANAM were applied. RESULTS: A total of 122 subjects were included in the analysis (51 pSS, 20 sSS and 51 controls); mean age of pSS was 56 years (SD 10.4), of which 47 (92.15%) were women. Moderate-severe cognitive impairment by MoCA was 17% in pSS, 5% in sSS, and 15% in controls, and by ANAM were 29% in pSS and 10% in sSS (P > .05). Visuospatial/executive subdomain in the MoCA was different between the pSS and the control group (P = .005). We encountered a statistically significant difference between pSS patients and control scores from the program in 6 of the 7 domains tested by the ANAM. CONCLUSION: No difference was found in the prevalence of cognitive impairment between pSS subjects and controls by MoCA. Several subdomain scores differed between groups in both scales. Evaluation of cognitive disorders in patients with SS, even in early stages of the disease, seems advisable but the best strategy is yet to be elucidated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".