A pilot study of oxidative pathways in MS fatigue: randomized trial of N‐acetyl cysteine
Bibliographic record
Abstract
OBJECTIVE: To assess feasibility, tolerability, and safety of N-acetyl cysteine (NAC) for fatigue in progressive MS. Secondary objectives evaluated changes in fatigue and oxidative pathway biomarkers on NAC versus placebo. METHODS: Individuals with progressive MS with Modified Fatigue Impact Scale (MFIS) > t38 were randomized 2:1 to NAC 1250mg TID or placebo for 4 weeks. The primary outcome was tolerability and safety. The secondary outcome to evaluate efficacy was MFIS change from baseline to week 4 between groups. Exploratory biomarker outcomes included change in blood GSH/GSSG ratio (reduced-to-oxidized glutathione (GSH)) and in vivo relative GSH using 7T MR spectroscopy (MRS) between groups. Fisher exact test was used for categorical and rank sum for continuous outcomes. RESULTS: Fifiteen were randomized (10 NAC, 5 placebo; mean age 56.1 years, 80% female, median EDSS 6.0). At least one adverse event (AE) occurred in 60% on NAC versus 80% on placebo (p = 0.75). There were two AEs attributed to NAC in one patient (abdominal pain and constipation), with 94% adherence to NAC. MFIS decreased in both groups at week 4, with the mean improvement of 11-points on NAC versus 18-points on placebo (p = 0.33). GSH/GSSG ratio decreased on placebo (-0.6) and NAC (-0.1) (p = 0.18). Change in GSH levels to total creatine in anterior and posterior cingulate cortex, insula, caudate, putamen, and thalamus did not differ between groups. INTERPRETATION: NAC was well-tolerated in progressive MS, although reduction in fatigue on NAC was similar to placebo. Antioxidant blood and MRS biomarkers were not significantly altered by NAC, which could be due to dose, route of administration, time of sample collection, short half-life, or lack of effect. REGISTERED: clinicaltrials.gov NCT02804594.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".