Ethyl-EPA in Huntington disease
Bibliographic record
Abstract
BACKGROUND: Preliminary evidence suggests beneficial effects of pure ethyl-eicosapentaenoate (ethyl-EPA) in Huntington disease (HD). METHODS: A total of 135 patients with HD were randomized to enter a multicenter, double-blind, placebo-controlled trial on the efficacy of 2 g/d ethyl-EPA vs placebo. The Unified Huntington's Disease Rating Scale (UHDRS) was used for assessment. The primary end point was outcome at 12 months on the Total Motor Score 4 subscale (TMS-4). Analysis of covariance (ANCOVA) and a chi2 test on response, defined as absence of increase in the TMS-4, were performed. RESULTS: A total of 121 patients completed 12 months, and 83 did so without protocol violations (PP cohort). Intent-to-treat (ITT) analysis revealed no significant difference between ethyl-EPA and placebo for TMS-4. In the PP cohort, ethyl-EPA proved better than placebo on the chi2 test on TMS-4 (p < 0.05), but missed significance on ANCOVA (p = 0.06). Secondary end points (ITT cohort) showed no benefit of ethyl-EPA but a significantly worse outcome in the behavioral severity and frequency compared with placebo. Exploring moderators of the efficacy of ethyl-EPA on TMS-4 showed a significant interaction between treatment and a factor defining patients with high vs low CAG repeats. Reported adverse events were distributed equally between treatment arms. CONCLUSIONS: Ethyl-eicosapentaenoate (ethyl-EPA) (purity > 95%) had no benefit in the intent-to-treat cohort of patients with Huntington disease, but exploratory analysis revealed that a significantly higher number of patients in the per protocol cohort, treated with ethyl-EPA, showed stable or improved motor function. Further studies of the potential efficacy of ethyl-EPA are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".