Cognitive impairment in Neuromyelitis Optica Spectrum Disorder: A retrospective study using the Brief International cognitive Assessment for Multiple Sclerosis (BICAMS)
Bibliographic record
Abstract
BACKGROUND: Neuromyelitis Optica Spectrum Disorder (NMOSD) is an inflammatory disease of the central nervous system. The study aimed to characterize the neuropsychological profile of NMOSD by comparing them with multiple sclerosis (MS) patients and healthy controls. METHOD: Sixty-four participants were included:19 NMOSD, 27 MS, and 18 healthy controls. The neuropsychological protocol included the Portuguese version of Montreal Cognitive Assessment, the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS), Verbal Fluency (phonemic and semantic), the Hospital Anxiety and Depression Scale, and the Expanded Disability Status Scale for clinical groups. RESULTS: NMOSD patients had significant lower cognitive performance when compared to HC mainly in information processing speed, concentration, language processing, and in executive functions (cognitive flexibility, sustained, and divided attention). No significant differences were observed between NMOSD and MS patients. Three predictors for cognitive impairment, according to BICAMS criteria, were found: depression, disease duration, and the level of disability. CONCLUSION: The neuropsychological profile found in the present study for NMOSD is consistent with the previous findings. Information regarding the predictors of cognitive impairment in both diseases and their different associations are important for future research and for guiding interventions more suitable for the neuropsychological needs of affected patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".