Recommendations for cognitive screening and management in multiple sclerosis care
Bibliographic record
Abstract
PURPOSE: To promote understanding of cognitive impairment in multiple sclerosis (MS), recommend optimal screening, monitoring, and treatment strategies, and address barriers to optimal management. METHODS: The National MS Society ("Society") convened experts in cognitive dysfunction (clinicians, researchers, and lay people with MS) to review the published literature, reach consensus on optimal strategies for screening, monitoring, and treating cognitive changes, and propose strategies to address barriers to optimal care. RECOMMENDATIONS: Based on current evidence, the Society makes the following recommendations, endorsed by the Consortium of Multiple Sclerosis Centers and the International Multiple Sclerosis Cognition Society: Increased professional and patient awareness/education about the prevalence, impact, and appropriate management of cognitive symptoms. For adults and children (8+ years of age) with clinical or magnetic resonance imaging (MRI) evidence of neurologic damage consistent with MS: As a minimum, early baseline screening with the Symbol Digit Modalities Test (SDMT) or similarly validated test, when the patient is clinically stable; Annual re-assessment with the same instrument, or more often as needed to (1) detect acute disease activity; (2) assess for treatment effects (e.g. starting/changing a disease-modifying therapy) or for relapse recovery; (3) evaluate progression of cognitive impairment; and/or (4) screen for new-onset cognitive problems. For adults (18+ years): more comprehensive assessment for anyone who tests positive on initial cognitive screening or demonstrates significant cognitive decline, especially if there are concerns about comorbidities or the individual is applying for disability due to cognitive impairment. For children (<18 years): neuropsychological evaluation for any unexplained change in school functioning (academic or behavioral). Remedial interventions/accommodations for adults and children to improve functioning at home, work, or school.
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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 | 0.023 | 0.115 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.010 | 0.007 |
| Research integrity | 0.021 | 0.024 |
| Insufficient payload (model declined to judge) | 0.027 | 0.014 |
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".