Effects of Pridopidine on Functional Capacity in Early-Stage Participants from the PRIDE-HD Study
Bibliographic record
Abstract
BACKGROUND: No pharmacological treatment has been demonstrated to provide a functional benefit for persons with Huntington's disease (HD). Pridopidine is a sigma-1-receptor agonist shown to have beneficial effects in preclinical models of HD. OBJECTIVE: To further explore the effect of pridopidine on Total Functional Capacity (TFC) in the recent double-blind, placebo-controlled PRIDE-HD study. METHODS: We performed post-hoc analyses to evaluate the effect of pridopidine on TFC at 26 and 52 weeks. Participants were stratified according to baseline TFC score and analyzed using repeated measures (MMRM) and multiple imputation assuming missing not-at-random (MNAR) and worst-case scenarios. RESULTS: The pridopidine 45 mg bid dosage demonstrated a beneficial effect on TFC for the entire population at week 52 of 0.87 (nominal p = 0.0032). The effect was more pronounced for early HD participants (HD1/HD2, TFC = 7-13), with a change from placebo of 1.16 (nominal p = 0.0003). This effect remained nominally significant using multiple imputation with missing not at random assumption as a sensitivity analysis. Responder analyses showed pridopidine 45 mg bid reduced the probability of TFC decline in early HD patients at Week 52 (nominal p = 0.02). CONCLUSION: Pridopidine 45 mg bid results in a nominally significant reduction in TFC decline at 52 weeks compared to placebo, particularly in patients with early-stage HD.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".