Abstract TP14: Final Infarct Volume as an Early Indicator the Clinical Outcome: Insight from ESCAPE Trial
Bibliographic record
Abstract
Background and Purpose: The goal of reperfusion therapy in acute ischemic stroke is to limit the extension of the ischemic core. The objectives of the present study were to assess the relationship between endovascular treatment and final infarct volume. Methods and Results: ESCAPE is a multicenter prospective randomized open-label trial with blinded outcome evaluation that enrolled 315 patients (endovascular treatment n=165; control n=150). Of these, 314 patient infarct volumes at 24 hours on CT or MRI were measured blinded to clinical data. Because infarct volumes were non-normally distributed, final infarct volumes were analysed by quartiles. Final infarct volumes were compared by treatment assignment and recanalization/reperfusion status measured by 2-8h CT angiogram in the control group and by formal angiography in the intervention arm. Results: Median final infarct volume among all study participants was 21 mL (IQR: 7 to 72). Median final infarct volume in endovascular treatment arm at 15.5 mL (IQR: 5 to 46.5) was significantly lower than median final infarct volume in control arm 33.5 mL (IQR: 11 to 95; P=0.0004). Small infarcts, defined as 1st quartile of infarct volumes were more common in the endovascular group compared to control (relative risk [RR] 1.5, CI95 1.02-2.3). Successful recanalization and reperfusion was highly associated with small infarcts (RR 2.2, CI95 1.4-3.4). The proportion of large hemispheric stroke (defined as an infarct volume in the 4th quartile) was much less frequent in the endovascular treatment arm (RR 0.6, CI95 0.3-0.8). Conclusions: This analysis supports the primary results of ESCAPE trial as endovascular treatment was associated with significantly smaller final infarct volumes. Recanalization/reperfusion was associated with smaller final infarct volume.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".