Mechanical Thrombectomy in Acute Ischemic Stroke: Angiographic Predictors of Outcome
Bibliographic record
Abstract
Background: In patients with acute ischemic stroke with large vessel occlusion, various angiographic features are important in patient selection and predicting outcome. Objective: We evaluated angiographic features like collaterals, clot burden score, angiographic recanalization, number of passes, and intracranial atherosclerotic disease (ICAD) with the functional outcome at 90 days. Materials and Methods: This was a retrospective analysis of prospectively collected data of 163 patients with acute ischemic stroke with large vessel occlusion who underwent mechanical thrombectomy within 24 hours of symptom onset. Angiographic data were reviewed blinded to clinical data. The outcome was defined as modified Rankin scale (mRS) at 90 days (good outcome mRS ≤2). Results: The median age of patients was 60 years and 34.4% were females. The median National Institutes of Health Stroke Scale (NIHSS) and Alberta Stroke Programme Early CT Score (ASPECTS) at admission were 17 and 6, respectively. On bivariate analysis, ASPECTS was >6, clot burden score was ≥7, recanalization of TICI was ≥2b, absence of ICAD, showed a positive correlation with the good outcome at 90 days (P-values of 0.003, 0.0001, and 0.03, respectively). Multiple attempts of device passes were associated with poor recanalization (P = 0.001) and it was seen more in ICAD patients. On multivariate analysis, independent predictors of poor outcome were clot burden score <7 (P = 0.043) and TICI score <2b (P = 0.048). Out of 41 patients (26%) with ICAD, 29 had a poor outcome at 90 days. Conclusion: Lower clot burden and less degree of recanalization were associated with poor outcome in acute ischemic stroke due to Large vessel occlusion (LVO). The presence of ICAD also predicted poor outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".