Exploring the relationship between ischemic core volume and clinical outcomes after thrombectomy or thrombolysis
Bibliographic record
Abstract
Objective To assess whether complete reperfusion after IV thrombolysis (IVT-R) would result in similar clinical outcomes compared to complete reperfusion after endovascular thrombectomy (EVT-R) in patients with a large vessel occlusion (LVO). Methods EVT-R patients were matched by age, clinical severity, occlusion location, and baseline perfusion lesion volume to IVT-R patients from the International Stroke Perfusion Imaging Registry (INSPIRE). Only patients with complete reperfusion on follow-up imaging were included. The excellent clinical outcome rates at day 90 on the modified Rankin Scale (mRS) were compared between EVT-R vs IVT-R patients within quintiles of increasing baseline ischemic core and penumbral volumes. Results From INSPIRE, there were 141 EVT-R patients and 141 matched controls (IVT-R) who met the eligibility criteria. In patients with a baseline core <30 mL, EVT-R resulted in a lower odds of achieving an excellent outcome at day 90 compared to IVT-R (day 90 mRS 0–1 odds ratio 0.01, p < 0.001). The group with a baseline core <30 mL contained mostly patients with distal M1 or M2 occlusions, and good collaterals (p = 0.01). In patients with a baseline ischemic core volume >30 mL (internal carotid artery and mostly proximal M1 occlusions), EVT-R increased the odds of patients achieving an excellent clinical outcome (day 90 mRS 0–1 odds ratio 1.61, p < 0.001) and there was increased symptomatic intracranial hemorrhage in the IVT-R group with core >30 mL (20% vs 3% in EVT-R, p = 0.008). Conclusion From this observational cohort, LVO patients with larger baseline ischemic cores and proximal LVO, with poorer collaterals, clearly benefited from EVT-R compared to IVT-R alone. However, for distal LVO patients, with smaller ischemic cores and better collaterals, EVT-R was associated with a lower odds of favorable outcome compared to IVT-R alone.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".