The Relationship Between Diffuse Axonal Damage and Fatigue in Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Fatigue is a common and distressing symptom for patients with multiple sclerosis (MS). There is growing evidence that fatigue in MS has a central nervous system component. We hypothesized that diffuse cerebral axonal damage could be associated with fatigue and used proton magnetic resonance spectroscopy to noninvasively measure axonal damage or loss in the brains of patients with MS. OBJECTIVE: To assess the strength of the relationship between central brain N-acetylaspartate and fatigue. DESIGN: Data from 73 patients who had undergone proton magnetic resonance spectroscopy imaging and completed the Fatigue Severity Scale questionnaire were analyzed. RESULTS: The N-acetylaspartate-creatine ratio (NAA/Cr) was significantly lower in the high-fatigue group than the low-fatigue group (mean +/- SD, 2.69 +/- 0.29 and 2.99 +/- 0.33, respectively. P =.003). Independent of the Kurtzke Expanded Disability Status Scale, T2 lesion volume, age, and disease duration, NAA/Cr was significantly lower in the high-fatigue group as compared with the low-fatigue group. There was a statistically significant linear correlation between the Fatigue Severity Scale scores and NAA/Cr (Spearman rank rho = -0.361, P =.02). CONCLUSIONS: The results of this study, combined with those of others, suggest that widespread axonal dysfunction is associated with fatigue in MS. Increased recruitment of cortical areas and pathways in response to brain injury may be responsible for the patient's sense that the effort required to perform actions is disproportionately high.
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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 | 0.000 |
| 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".