The Use of Tenecteplase in Combination with Brain Scan Analysis in Thrombolysis of Acute Ischemic Stroke: A Moroccan Experience
Bibliographic record
Abstract
Objective: Intravenous thrombolysis of acute ischemic stroke uses alteplase, which has long been approved for this indication. In the same context, studies on Tenecteplase have demonstrated the efficacy and safety of this molecule, which we use in our structure following clinical and radiological evaluation using non-enhanced computed tomography. Our aim is to share our institutional approach. Materials and Methods: Retrospective, descriptive, cross-sectional study in the neurology department of Casablanca over a 5-year period from 01 January 2018 to 31 December 2022. We included all patients with suspected acute stroke who underwent IVT with Tenecteplase with an Alberta Stroke Program Early CT Score greater than or equal to 7 on non-enhanced cerebral computed tomography. The Modified Rankin Scale was evaluated at 3 months. Results: During these 5 years, 140 patients (49% were females) had received Tenecteplase thrombolytic therapy. The mean age was 67 years, mean National Institutes of Health Stroke Scale was 13/42, mean Alberta Stroke Program Early CT Score was 8/10. 97% of the patients received a dose of 0.25mg/kg of Tenecteplase in a mean time of 210min from the onset of symptoms. The Modified Rankin Scale between 0 and 2 at 3 months was in 46% and 13% of death. Conclusion: We are satisfied with the results of Intravenous thrombolysis with Tenecteplase. However, we are convinced of the limited information provided by a non-enhanced cerebral computed tomography to brain magnetic resonance imaging which remains difficult to access in our context.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".