A Randomised, Double-Blind, Placebo-Controlled Trial of Actovegin in Patients with Post-Stroke Cognitive Impairment: ARTEMIDA Study Design
Bibliographic record
Abstract
BACKGROUND: No drug treatment to date has shown convincing clinical evidence of restoring cognitive function or preventing further decline after stroke. The ongoing ARTEMIDA study will evaluate the efficacy and safety of Actovegin for the symptomatic treatment of post-stroke cognitive impairment (PSCI) and will explore whether Actovegin has any disease-modifying effect by assessing whether any changes are sustained after treatment. DESIGN: ARTEMIDA is a 12-month, multicentre trial in patients (planned a total of 500, now recruited) with cognitive impairment following ischaemic stroke. The study consists of a baseline screening (≤7 days after stroke), after which eligible patients are randomised to Actovegin (2,000 mg/day for up to 20 intravenous infusions followed by 1,200 mg/day orally) or placebo for a 6-month double-blind treatment period. Patients will be followed up for a further 6 months, during which time they will be treated in accordance with standard clinical practice. The primary study endpoint is change from baseline in the Alzheimer's Disease Assessment Scale, cognitive subscale, extended version. Secondary outcomes include: Montreal Cognitive Assessment; dementia diagnosis (ICD-10); National Institutes of Health Stroke Scale; Barthel Index; EQ-5D; Beck Depression Inventory, version II, and safety. CONCLUSION: There is a clear need for effective treatments for PSCI. ARTEMIDA should provide important insights into the use of a novel drug therapy for PSCI.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".