Intra-arterial therapy following intravenous alteplase for severe ischemic stroke
Bibliographic record
Abstract
P190 Background Intravenous alteplase may not be efficacious for the majority of patients with proximal large vessel occlusion. Intra-arterial thrombolysis improves outcome in MCA occlusion but delays occur between the decision to proceed to interventional therapy and its application. Initial administration of intravenous alteplase prior to an intra-arterial approach may provide better outcomes due to earlier exposure of thrombus to alteplase and subsequently improved re-canalisation rates. Criteria for patient selection are undefined. Methods Case series with 90d outcomes. Between February 1999 and July 2000, 7 patients ranging in age from 40–84 years were treated with an IV/IA approach. All patients received IV alteplase within 3h of stroke onset. Two patients had basilar occlusions and six had MCA M1 stem or one or both M2 branch occlusions. Patients were selected using one or both of pre-treatment TCD examination (n=5) or large DWI/PWI mismatch with MRA documented occlusion (n=3). One patient with an MCA occlusion had severe vessel tortuosity and did not receive IA alteplase because access to the thrombus was not possible. Results The median NIHSS score was 19 (range 10–24). Intra-arterial therapy was started between 2–3h of symptom onset in all cases. Angiographic recanalisation was successful in all patients who had an intervention (6 of 7 patients). One patient underwent vertebral artery angioplasty instead of thrombolysis. Two patients died or were severely disabled (mRS 5–6), one from contralateral recurrent MCA stroke several days post-procedure and one with a severe basilar artery stroke. The remaining 4 patients with MCA occlusions had excellent neurological outcomes and were independent at 90d. There were no symptomatic hemorrhages. Conclusions Selection of patients for IV/IA therapy is aided by early cerebrovascular imaging. IV/IA therapy can be performed within 3h of stroke onset and can result in excellent outcomes for patients with the most severe of ischemic strokes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".