MIDAS (Modafinil in Debilitating Fatigue after Stroke): a randomized, double-blind, placebo-controlled, cross-over trial
Bibliographic record
Abstract
Background and Purpose: This study aimed to assess the efficacy of modafinil, a wakefulness-promoting agent in alleviating post-stroke fatigue ≥3 months after stroke. We hypothesized that 200 mg of modafinil daily for 6 weeks would result in reduced symptoms of fatigue compared with placebo. Methods: This single-center phase 2 trial used a randomized, double-blind, placebo-controlled, crossover design. The key inclusion criterion was a multidimensional fatigue inventory score of ≥60. Patients were randomized to either modafinil or placebo for 6 weeks of therapy, then after a 1 week washout period swapped treatment arms for a second 6 weeks of therapy. The primary outcome was the multidimensional fatigue inventory; secondary outcomes included the Montreal cognitive assessment, the Depression, Anxiety, and Stress Scale (DASS), and the Stroke-Specific Quality of Life (SSQoL) scale. The multidimensional fatigue inventory is a self-administered questionnaire with a range of 0 to 100. Treatment efficacy was assessed using linear regression by estimating within-person, baseline-adjusted differences in mean outcomes after therapy. This trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000350527). Results: A total of 232 stroke survivors were screened and 36 were randomized. Participants receiving modafinil reported a significant decrease in fatigue (multidimensional fatigue inventory, -7.38; 95% CI, -21.76 to -2.99; P < 0.001) and improved quality of life (SSQoL, 11.81; 95% CI, 2.31 to 21.31; P=0.0148) compared with placebo. Montreal cognitive assessment and DASS were not significantly improved with modafinil therapy during the study period (P > 0.05). Conclusions: Stroke survivors with nonresolving fatigue reported reduced fatigue and improved quality of life after taking 200 mg daily treatment with modafinil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.008 | 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".