Montreal cognitive assessment as a screening instrument for cognitive impairment in systemic lupus erythematosus patients without overt neuropsychiatric manifestations
Bibliographic record
Abstract
OBJECTIVES: The Montreal Cognitive Assessment (MoCA) is an increasingly used screening tool for cognitive impairment. The aim of this study was to examine how MoCA performed in identifying cognitive impairment (CI) domains in SLE patients compared with formal standardized neuropsychological testing (NPT). Factors related to SLE disease, immunologic and psychological state associated with CI were also explored. METHODS: This cross-sectional study recruited 50 SLE patients without overt neuropsychiatric manifestations from April 2017 to May 2018. The patients were evaluated with MoCA, formal NPT and the Depression, Anxiety, and Stress Scales (DASS) 42-item self-report questionnaire. Values of sensitivity and specificity were computed for different cut-offs of MoCA within each cognitive domain of NPT and descriptive analysis was used to identify the factors affecting cognitive function. RESULTS: The median score for MoCA was 27.5 (range 22-30). Using a MoCA cutoff of <26, 18 (36%) were identified to have CI using NPT compared to 8 (16%) using MoCA. The most frequently affected cognitive domain was executive functioning with 15 affected patients. Sensitivities and specificities of the MoCA range from 50% to 100% and 5.7% to 16.7%, respectively, across cognitive domains. A lower MoCA cutoff of <25 improve sensitivity of identifying impairment in executive functioning from 60% to 80%. In univariate analysis, DASS scores, disease activity, presence of antiphospholipid antibodies, presence of concurrent autoimmune disease, current, and cumulative corticosteroid therapy did not predict cognitive performance. CONCLUSION: MoCA may be a useful screening tool to identify the most frequently affected cognitive domain which is executive functioning using a lower cutoff of <25 in SLE patients without overt neuropsychiatric manifestations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".