Safety and Real-World Effectiveness in the Transition from Alteplase to Tenecteplase for Stroke Treatment
Bibliographic record
Abstract
BACKGROUND: Tenecteplase has been shown to be non-inferior to alteplase for the treatment of acute ischemic stroke within 4.5 hours of stroke onset. While not formally approved by regulatory authorities, many jurisdictions have transitioned to using tenecteplase for routine stroke treatment because it is simpler to use and has cost advantages. METHODS: We report a three-phase time-series analysis over 2.5 years and the process for transition from use of alteplase to tenecteplase for the routine treatment of acute ischemic stroke from a system-wide perspective involving an entire province. The transition was planned and implemented centrally. Data were collected in clinical routine, arising from both administrative sources and a prospective stroke registry, and represent real-world outcome data. Data are reported using standard descriptive statistics. RESULTS: A total of 1211 patients were treated with intravenous thrombolysis (477 pre-transition using alteplase, 180 transition period using both drugs, 554 post-transition using tenecteplase). Baseline characteristics, adverse events and outcomes were similar between epochs. There were four dosing errors with tenecteplase, including providing the cardiac dose to two patients. There were no instances of major hemorrhage associated with dosing errors. DISCUSSION: The transition to using intravenous tenecteplase for stroke treatment was seamless and resulted in identical outcomes to intravenous alteplase.
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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 | 0.015 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".