Worldwide Survey on Approach to Thrombolysis in Acute Ischemic Stroke With Large Vessel Occlusion
Bibliographic record
Abstract
Background and Objectives: With recent trials suggesting that endovascular thrombectomy (EVT) alone may be noninferior to combined intravenous thrombolysis (IVT) with alteplase and EVT and that tenecteplase is non-inferior to alteplase in treating acute ischemic stroke, we sought to understand current practices around the world for treating acute ischemic stroke with large vessel occlusion (LVO) depending on the center of practice (IVT-capable vs IVT and EVT-capable stroke center). Methods: The electronic survey launched by the Practice Current section of Neurology: Clinical Practice included 6 clinical and 8 demographic questions. A single-case scenario was presented of a 65-year-old man presenting with right hemiplegia with aphasia with a duration of 1 hour. Imaging showed left M1-MCA occlusion with no early ischemic changes. The respondents were asked about their treatment approach in 2 settings: the patient presented to (1) the IVT-only capable center and (2) the IVT and EVT-capable center. They were also asked about the thrombolytic agent of choice in current and ideal circumstances for these settings. Results: A total of 203 physicians (42.9% vascular neurologists) from 44 countries completed the survey. Most participants (55.2%) spent ≥50% of their time delivering stroke care. The survey results showed that in current practice, more than 90% of respondents would offer IVT + EVT to patients with LVO stroke presenting to either an EVT-capable (91.1%) or IVT-only-capable center (93.6%). Although nearly 80% currently use alteplase for thrombolysis, around 60% would ideally like to switch to tenecteplase independent of the practice setting. These results were similar between stroke and non-stroke neurologists. Discussion: Most physicians prefer IVT before EVT in patients with acute ischemic stroke attributable to large vessel occlusion independent of the practice setting.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".