Detecting isolated cognitive relapses in persons with MS
Bibliographic record
Abstract
BACKGROUND: The existence of isolated cognitive relapses (ICRs) in persons with MS (PwMS) has been debated. OBJECTIVE: To examine relapses with decline on Symbol Digit Modalities Test (SDMT) but no change on Expanded Disability Status Scale (EDSS). METHODS: This 3-year prospective cohort study identified PwMS experiencing a relapse with decrease on SDMT. Participants with SDMT decline/stable EDSS were labeled "ICR," while those with a corresponding decrease on EDSS were classified "Relapse with Cognitive Decline (RCD)." Two definitions of SDMT decline were explored: (1) ⩾ 8 points, and (2) ⩾ 4 points. Logistic regression was used to analyze the relationship between ICR and RCD. RESULTS: = 0.024) using demographics and disease characteristics explained 28.4% of the variance in ICR versus RCD. Only the MS Neuropsychological Questionnaire was associated with ICR (odds ratio (OR): 8.6; 95% confidence interval (CI): 1.1-16.4) 40 relapsing participants with SDMT decrease of ⩾ 4 points were identified: 26 (65%) had a stable EDSS (ICR). Logistic regression did not find any variable predictive of ICR. CONCLUSION: This prospective study demonstrates evidence of ICR in PwMS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".