Abstract MP5: Intravenous Thrombolysis With Tenecteplase in Patients With Large Vessel Occlusions: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Accumulating evidence from randomized-controlled clinical trials (RCTs) suggest that tenecteplase may represent an effective treatment alternative to alteplase for acute ischemic stroke (AIS). In the present systematic review and meta-analysis we sought to compare the efficacy and safety outcomes of intravenous tenecteplase to intravenous alteplase administration for AIS patients with large vessel occlusions (LVO). Methods: We searched MEDLINE and Scopus for published RCTs providing outcomes of AIS with confirmed LVO receiving intravenous thrombolysis with either tenecteplase at different doses or alteplase at standard dose 0.9mg/kg. The primary outcome was the odds of modified Rankin Scale (mRS) score of 0-2 at 3 months. Results: We included 4 RCTs including a total of 433 patients. Patients with confirmed LVO receiving tenecteplase had higher odds of successful recanalization (OR=3.05, 95%CI: 1.73-5.40; Figure A), mRS scores of 0-2 [odds ratio (OR)=2.06, 95%CI: 1.15-3.69; Figure B], and functional improvement defined as 1-point decrease across all mRS grades (common OR=1.84, 95%CI: 1.18-2.87; Figure C) at 3 months compared to patients with confirmed LVO receiving alteplase. There was little or no heterogeneity between the results provided from included studies regarding the aforementioned outcomes (I 2 ≤20%). No difference in the outcomes of early neurological improvement, symptomatic intracranial hemorrhage (ICH), any ICH and the rates of mRS 0-1 or all-cause mortality at 3 months were detected between patients with LVO receiving intravenous thrombolysis with either tenecteplase or alteplase. Conclusion: AIS patients with LVO receiving intravenous thrombolysis with tenecteplase have significantly better recanalization and clinical outcomes compared to patients receiving 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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".