Implication of Deep Versus Cortical Ischemia on DWI-ASPECTS In Anterior Circulation Large Vessel Occlusion Ischemic Stroke (P3.083)
Bibliographic record
Abstract
Objective: The aim of this study is to assess whether deep and cortical ischemia, as calculated by the Alberta Stroke Program Early CT Score (ASPECTS), equally predict poor clinical outcome in anterior circulation large vessel occlusion (ACLVO) acute ischemic stroke. Background: ASPECTS is a commonly utilized selection criteria for endovascular therapy in ACLVO stroke, including in ongoing clinical trials. The ten-point topographical scoring system consists of 3 deep regions (caudate, lentiform nucleus, internal capsule) and 7 cortical regions (insula, M1-6), which are equally valued. Design/Methods: Patients with intracranial ICA, M1 and M2 occlusions who underwent endovascular therapy at UPMC between 2007-2014 were included in our analysis. Baseline demographics and outcomes including final infarct volume (FIV), hemorrhagic transformation, and 3-month modified Rankin Scale (mRS) scores were collected. DWI-ASPECTS was independently calculated on follow-up MRI (12-72 hours post-treatment) by two observers. The impact of ischemia in cortical and deep ASPECTS regions on poor clinical outcome (mRS 3-6) was assessed through logistic regression analysis. Results: 213 patients were included in the analysis (mean age 66.1±1.0 yrs, median NIHSS 15 [IQR 11-18], 3-month poor outcome rate=46.8[percnt]). Inter-rater reliability was good for DWI-ASPECTS regions (deep: Kappa=0.72; cortical: Kappa=0.63). Ischemia in cortical ASPECTS regions (OR 1.80, 95[percnt] CI 1.48-2.17, p<0.001) and deep ASPECTS regions (OR 1.57, 95[percnt] CI 1.15-2.14, p=0.005) were independent predictors of poor outcome. After controlling for FIV, both variables remained independent predictors of poor outcome (cortical: OR 1.61, 95[percnt] CI 1.28-2.03, p < 0.001; deep: OR 1.59, 95[percnt] CI 1.15-2.20, p=.005). Conclusions: Deep and cortical ischemic lesions defined by ASPECTS regions were independent predictors of poor outcome in ACLVO stroke. We did not observe a statistically significant difference between cortical and deep ischemia on clinical outcomes. Validation in a larger cohort is needed to confirm these findings.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".