Abstract WP47: Reperfusion Following Ischemic Stroke is Associated with Reduced Brain Edema
Bibliographic record
Abstract
Introduction: Revascularization is a robust therapy for acute ischemic stroke, but animal studies suggest that reperfusion edema may attenuate its beneficial effects. In stroke patients, early reperfusion consistently reduces infarct volume and improves long-term functional outcome, but there is little clinical data available regarding reperfusion edema. We sought to elucidate the relationship between reperfusion and brain edema in a patient cohort of moderate to severe stroke. Methods: Seventy-one patients enrolled in the Echoplanar Imaging Thrombolysis Evaluation Trial (EPITHET) with serial brain magnetic resonance imaging and perfusion-weighted imaging (PWI) were analyzed. Reperfusion percentage was calculated based on the difference in PWI lesion volume at baseline and follow-up (day 3-5). Midline shift (MLS) was measured on the day 3-5 fluid attenuated inversion recovery (FLAIR) sequence. Swelling volume and infarct growth volume were assessed using region-of-interest analysis on the baseline and follow-up DWI scans based on our prior methods. Results: Greater percentage of reperfusion was associated with less MLS (Spearman ρ = -0.46; P <0.0001) and reduced swelling volume (Spearman ρ = -0.56; P <0.0001). In multivariate analysis, reperfusion was an independent predictor of less MLS ( P <0.006) and decreased swelling volume ( P <0.0054), after adjusting for age, baseline NIHSS, admission blood glucose, baseline DWI volume, and IV tPA treatment. Conclusions: Reperfusion is associated with reduced brain edema as measured by MLS and swelling volume. While our data do not exclude the possibility of reperfusion edema in certain circumstances, in stroke patients, reperfusion following acute stroke is predominantly linked to less brain swelling.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".