Abstract P338: Incidence, Predictors and Impact of Infarct in New Territory in Escape Na1 Trial
Bibliographic record
Abstract
Introduction: Infarct in new territory (INT) is a known complication of endovascular therapy. We assessed the prevalence, predictors and clinical relevance of INT Methods: We included patients from the ESCAPE-NA1: a multicenter, international randomized study that assessed the efficacy of intravenous nerinetide in patients with acute ischemic stroke who underwent EVT within 12 hours from onset. All imaging was re-evaluated, and INT was defined by presence of infarct in new vascular territory, outside the baseline target occlusion(s) on follow up CT and MRI. INT’s were classified by maximum diameter (<2mm, 2-20mm and >20mm) and location. Results: Of 1099 analyzed patients in ESCAPE NA1, 107 had INT (9.7%, mean age 67 years, 51.4% females). There were no differences at baseline in those with vs without INT. Most INTs (75.7%) were angiographically occult and 41(38.3%) were > 20mm. The most common INT territory was the ACA alone or in combination with MCA/PCA (30.3%). The presence of emboli in new territory angiographically was significantly associated with INT (OR 16.39, 95%CI 8.14-33.09). Alteplase use, balloon guide catheter use, nerinetide and initial occlusion site did not predict INT. INT patients had higher final median infarct volumes compared to non-INT (44.5cc vs 23.3cc, P<0.001). Large INT (diameter of >20mm) were associated with poor clinical outcome compared to INT (<2mm) OR (mRS 0-2) 0.17, 95%CI 0.05-0.55). Conclusion: Infarcts in new territory are common and are associated with poor outcome.
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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 | 0.001 | 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".