Intra-arterial thrombolysis in acute ischemic stroke: a review of pharmacologic approaches
Bibliographic record
Abstract
Ischemic stroke is a major public health problem worldwide. The potential to cure stroke patients with intravenous thrombolytic therapy has evolved to the use of intra-arterial thrombolytic agents. Fewer than 200 patients have been enrolled in randomized trials of intra-arterial therapy. In this article the authors have reviewed the literature listed in MEDLINE and EMBase, and searched relevant articles to examine the role of fibrinolytic agents in acute interventional stroke therapy. Only English language articles reporting five or more patients were included. Outcomes were defined at 90 days. Good outcome was defined on the modified Rankin Scale. Symtpomatic hemorrhage was defined as hemorrhage in the setting of clinical deterioration in the first 24 to 48 h. The search identified 57 studies of which 44 reported usable data. Only three randomized trials were reported. Of a total of 1140 patients, most (73%) were treated open-label with urokinase (Abbokinase, Abbott Laboratories). The best outcomes were reported in case series and slightly worse outcomes were reported in clinical trials. Overall, it was not possible to distinguish whether one agent was superior to the others. There is a paucity of published evidence on intra-arterial therapy for acute ischemic stroke. Alteplase (Activase, Genentech Inc.) is currently the drug of choice simply because it is available and it is the current intravenous standard. Further trials and developments are anticipated.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.012 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".