Intra-arterial Thrombolysis of Embolic Middle Cerebral Artery Using Collateral Pathways
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cervical internal carotid artery (ICA) occlusion associated with middle cerebral artery (MCA) embolic occlusion requires prompt revascularization to prevent devastating stroke. With the advent of endovascular techniques for chemical and mechanical thrombolysis, the clinical outcome of patients with major arterial occlusions will improve. Finding the most expedient pathway to the site of end organ occlusion for thrombolysis is important. METHODS: We present two cases of acute stroke secondary to thrombotic occlusion of the cervical ICA associated with MCA embolic occlusion treated with intra-arterial thrombolysis via catheter navigation through the posterior communicating artery to the site of MCA arterial occlusion. No attempt was made to transverse the occluded ICA. RESULTS: Near complete restoration of flow was achieved in one patient and minimal vessel reopening was observed in the other patient. Both patients had good outcomes. CONCLUSION: Intra-arterial thrombolysis via Circle of Willis collaterals such as the posterior communicating artery for the treatment of acute thrombotic occlusion of the cervical internal carotid artery associated with embolic occlusion of the middle cerebral artery is a therapeutic option. This treatment option avoids the potential complications of navigating through an occluded proximal internal carotid artery and may expedite reopening of the MCA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".