Thrombolysis in Mild Stroke
Bibliographic record
Abstract
Background and Purpose: Mild ischemic stroke patients enrolled in randomized controlled trials of thrombolysis may have a different symptom severity distribution than those treated in routine clinical practice. Methods: We compared the distribution of the National Institutes of Health Stroke Scale (NIHSS) scores, neurological symptoms/severity among patients enrolled in the PRISMS (Potential of r-tPA for Ischemic Strokes With Mild Symptoms) randomized controlled trial to those with NIHSS score ≤5 enrolled in the prospective MaRISS (Mild and Rapidly Improving Stroke Study) registry using global P values from χ2 analyses. Results: Among 1736 participants in MaRISS, 972 (56%) were treated with alteplase and 764 (44%) were not. These participants were compared with 313 patients randomized in PRISMS. The median NIHSS scores were 3 (2–4) in MaRISS alteplase-treated, 1 (1–3) in MaRISS non–alteplase-treated, and 2 (1–3) in PRISMS. The percentage with an NIHSS score of 0 to 2 was 36.3%, 73.3%, and 65.2% in the 3 groups, respectively (P<0.0001). The proportion of patients with a dominant neurological syndrome (≥1 NIHSS item score of ≥2) was higher in MaRISS alteplase-treated (32%) compared with MaRISS nonalteplase-treated (13.8%) and PRISMS (8.6%; P<0.0001). Conclusions: Patients randomized in PRISMS had comparable deficit and syndromic severity to patients not treated with alteplase in the MaRISS registry and lesser severity than patients treated with alteplase in MaRISS. The PRISMS trial cohort is representative of mild patients who do not receive alteplase in current broad clinical practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".