Tenecteplase vs Alteplase in Acute Ischemic Stroke Within 4.5 Hours
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The current European Stroke Organisation expedited recommendation on tenecteplase (TNK) for acute ischemic stroke (AIS) advocates that TNK 0.25 mg/kg can be used alternatively to alteplase (tissue plasminogen activator [TPA]) for AIS of <4.5 hours duration, based on a meta-analytical approach establishing noninferiority. Since the publication of these guidelines, 4 additional randomized controlled clinical trials (RCTs) have provided further insight. METHODS: We conducted an updated systematic review and meta-analysis including all available RCTs that investigated efficacy and safety of TNK 0.25 mg/kg compared with TPA for the treatment of AIS within 4.5 hours of onset. The primary outcome was defined as the excellent functional outcome at 3 months (modified Rankin Scale [mRS] score 0-1), whereas good functional outcome (mRS score 0-2), reduced disability at 3 months (≥1-point reduction across all mRS scores), symptomatic intracranial hemorrhage (sICH), and 3-month mortality were evaluated as secondary outcomes. Pooled estimates were calculated with random-effects model. A prespecified subgroup analysis was performed stratifying for TNK formulation, that is, original TNK vs biocopy: recombinant human TNK tissue-type plasminogen activator that is available in China and has a different production process. RESULTS: = 0%). DISCUSSION: The updated meta-analysis confirms similar safety between TNK 0.25 mg/kg and TPA, while showing that TNK is superior to TPA regarding excellent functional outcome and reduced disability at 3 months. These findings support transitioning to TNK in clinical practice.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.020 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".