Tenecteplase in Acute Ischemic Stroke: A Scientific Statement From the Korean Stroke Society
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Tenecteplase (TNK) is a promising alternative thrombolytic agent for the treatment of acute ischemic stroke (AIS). However, its potential use is being impeded by the lack of regulatory approval and reimbursement policies for TNK in AIS in many countries, including South Korea. To address this therapeutic gap, the Korean Stroke Society developed scientific statement intended to inform policy changes and support the introduction of TNK in regions where it is not yet accessible, with the aim of enabling AIS patients to benefit from this advancement in thrombolytic therapy. METHODS: We reviewed randomized controlled trials (RCTs), meta-analyses, and systematic reviews published between January 2010 and November 2024 involving AIS patients treated with intravenous TNK. Meta-analyses were included if they exclusively evaluated RCTs and provided clinical evidence on the efficacy and safety of TNK. The statements were thoroughly reviewed and finalized by international expert panels after iterative revisions. RESULTS: The statements suggest that TNK at 0.25 mg/kg can be considered as an alternative to alteplase for intravenous thrombolysis within 4.5 hours of the onset of AIS. The clinical outcomes in patients with large-vessel occlusion who are candidates for endovascular thrombectomy are better for TNK at 0.25 mg/kg than for alteplase. CONCLUSIONS: These statements are intended to support the adoption of TNK in countries where it is not yet available, including South Korea, by providing up-to-date clinical evidence. Their implementation may broaden the therapeutic options for AIS patients and help align acute stroke care practices with international standards.
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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 | 0.106 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.009 |
| 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".