Recanalization following Endovascular treatment and imaging of PErfusion, Regional inFarction and atrophy to Understand Stroke Evolution—NA1 (REPERFUSE-NA1)
Bibliographic record
Abstract
RATIONALE: Following endovascular treatment, poor clinical outcomes are more frequent if the initial infarct core or volume of irreversible brain damage is large. Clinical outcomes may be improved using neuroprotective agents that reduce stroke volume and improve recovery. AIM: The aim of the REPERFUSE NA1 was to replicate the preclinical neuroprotection study that significantly reduced infarct volume in a primate model of ischemia reperfusion. Specifically, REPERFUSE NA1 will determine if administration of the neuroprotectant NA1 prior to endovascular therapy can significantly reduce early (Day 2 subtract Day 1 diffusion-weighted imaging volume) and delayed secondary infarct (90-day whole brain atrophy plus FLAIR volume-Day 1 diffusion-weighted imaging volume) growth, as measured by magnetic resonance imaging. METHODS AND DESIGN: REPERFUSE-NA1 is a magnetic resonance imaging observational substudy of ESCAPE-NA1 (ClinicalTrialGov NCT02930018). A total of 150 acute stroke patients will be recruited (including 20% attrition) that have been randomized to either NA1 or placebo in the ESCAPE-NA1 trial. STUDY OUTCOMES: Primary-Early infarct growth measured using diffusion-weighted imaging will be at least 30% smaller in patients receiving NA1 compared to placebo. Secondary-Delayed secondary stroke injury at 90 days will be significantly reduced in patients receiving NA1 compared to placebo, as well as delayed secondary growth at 90 days. CONCLUSION: REPERFUSE-NA1 will demonstrate the effect of NA1 neuroprotection on reducing the early and delayed stroke injury after reperfusion treatment.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".