Cognition in Early Relapsing-Remitting Multiple Sclerosis: Consequences May Be Relative to Working Memory
Bibliographic record
Abstract
The Relative Consequence Model proposes multiple sclerosis (MS) patients have a fundamental deficit in processing speed that compromises other cognitive functions. The present study examined the mediating role of processing speed,as well as working memory, in the MS-related effects on other cognitive functions for early relapsing-remitting patients. Seventy relapsing-remitting MS patients with disease duration not greater than 10 years and 72 controls completed tasks assessing processing speed, working memory, learning, and executive functioning. The possible mediating roles of speed and working memory in the MS-related effects on other cognitive functions were evaluated using structural equation modeling. Processing speed was not significantly related to group membership and could not have a mediating role. Working memory was related to group membership and functioned as a mediating/intervening factor. The results do not support the Relative Consequence Model in this sample and they challenge the notion that working memory impairment only emerges at later disease stages. The results do support a mediating/intervening role of working memory. These results were obtained for early relapsing-remitting MS patients and should not be generalized to the broader MS population. Instead, future research should examine the relations that exist at other disease stages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".