Cognitive impairment, fatigue and depression in multiple sclerosis: Is there a difference between benign and non-benign MS?
Bibliographic record
Abstract
INTRODUCTION: Multiple Sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system (CNS). The severity of disability in people with MS (PwMS) is generally measured with the Expanded Disability Status Scale (EDSS). A variant of MS known as 'benign MS' (BMS) has been defined as an EDSS score of 3 or lower, combined with a disease duration of 10 years or longer; however, there is disagreement in the field about whether BMS really exists. Given that the EDSS does not capture cognitive issues, communication dysfunction, fatigue, depression, or anxiety properly, its ability to accurately represent disability in all PwMS, including BMS, remains questionable. METHODS: In this study, 141 persons with BMS (PwBMS) were included, consisting of 115 females (82%) and 26 males (18%) with a mean age of 50.8 (±8.68). A computerized test battery (NeuroTrax®) was used to assess cognition, covering seven cognitive domains (memory, executive function, visual-spatial processing, verbal function, attention, information processing, and motor skills). Fatigue was measured using the Fatigue Severity Scale (FSS). The Beck Depression Inventory (BDI) was used to assess symptoms of depression. Cognitive impairment was defined for this study as when someone has a score lower than 85 in at least two subdomains of the cognitive test battery. Rates of impairment were compared to 158 persons with non-benign MS (PwNBMS; with a disease duration of 10 years and longer and an EDSS score higher than 3) and 487 PwMS with a disease duration of fewer than 10 years. RESULTS: Cognitive impairment was found in 38% of PwBMS and in 66% of PwNBMS (p<0.001). In PwBMS, the lowest rate of impairment was found in the verbal function domain (18%) and the highest rate of impairment in the domain of information processing (32%). Fatigue and depression were found in 78% and 55% of all PwBMS, with no difference in these rates between PwBMS and PwNBMS (p = 0.787 and p = 0.316 resp.) CONCLUSION: Cognitive impairment, fatigue and depression are common among people with an EDSS-based definition of benign MS. These aspects should be incorporated into a new and better definition of truly benign MS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".