The Mild and Rapidly Improving Stroke Study (MaRISS): Rationale and design
Bibliographic record
Abstract
RATIONALE: Although mild and rapidly improving stroke symptoms are the most common first stroke presentation, this group has been understudied in acute stroke trials. Observational and retrospective studies suggest residual disability in one third of patients. AIMS: To elucidate long-term outcomes of patients with mild and rapidly improving stroke, evaluate the predictors of outcome, and examine the association with alteplase treatment. SAMPLE SIZE: The initial estimate of 2650 participants to detect a 9% difference in non-disabled 90-day outcomes between alteplase-treated and untreated participants was revised to 2000 after a pre-planned re-estimation based on actual treatment rates. METHODS AND DESIGN: Prospective observational study of patients with mild ischemic stroke (NIHSS ≤ 5) or rapidly improving stroke symptoms evaluated within 4.5 h from onset. OUTCOMES: The primary outcome is the proportion of patients with modified Rankin Scale (mRS) ≥ 2 at 90 days; the primary safety outcome is symptomatic hemorrhagic transformation within 36 h among those treated with alteplase. Secondary outcomes include the 90-day Barthel Index, Stroke Impact Scale 16, European Quality of Life scale, mRS at 30 days, and 30- and 90-day mortality. DISCUSSION: MaRISS will define outcomes and their predictors and clarify the effects of alteplase in patients with mild and rapidly improving stroke symptoms, providing clinicians with important information to manage this population.
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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 | 0.032 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".