TESLA Trial: Rationale, Protocol, and Design
Bibliographic record
Abstract
Background: Mechanical thrombectomy has been shown to be effective in patients with acute ischemic stroke secondary to large-vessel occlusion and small to moderate infarct volume. However, there are no randomized clinical trials for large-core infarct volume comparing mechanical thrombectomy to medical therapy in the population selected based solely on noncontrast computed tomography brain scan. The TESLA (Thrombectomy for Emergent Salvage of Large Anterior Circulation Ischemic Stroke) randomized clinical trial is designed to address this clinical question. Methods: The TESLA trial aim is to demonstrate the efficacy (3-month and 1-year disability following stroke) and safety of intraarterial mechanical thrombectomy in patients with large-volume infarction assessed with a noncontrast computed tomography scan. The TESLA trial design is a prospective, randomized controlled, multicenter, open-label, assessor-blinded anterior circulation acute ischemic stroke trial with adaptive enrichment design, enrolling up to 300 patients. Patients with anterior circulation large-vessel occlusion who meet the imaging and clinical eligibility criteria with a large-core infarction on the basis of noncontrast computed tomography Alberta Stroke Program Early CT Score (2-5) adjudicated by a site investigator will be randomized in a 1:1 ratio to undergo intraarterial thrombectomy or best medical management up to 24 hours from last known well. Results: The primary efficacy outcome is utility-weighted modified Rankin Scale (mRS) score distribution at 90 days between the groups. The results will be based on an intention-to-treat analysis that will examine the Bayesian posterior probability that, adjusted for Alberta Stroke Program Early CT Score, patients with large-core infarct volume treated with intra-arterial thrombectomy have higher expected utility-weighted mRS than those treated with best medical management alone. The primary safety outcome is the 90-day death rate. Key secondary outcomes are dichotomized mRS 0 to 2 and 0 to 3 outcomes, ordinal mRS scores, and quality of life (EuroQol 5 Dimension 5 Level survey) at 90 days and 1 year, utility-weighted mRS at 1 year, hemicraniectomy rate, and rate of 24-hour symptomatic intracranial hemorrhage in both groups. Conclusion: TESLA is a pragmatic trial, designed to address the unanswered question of the efficacy and safety of intra-arterial thrombectomy in patients with large infarcts diagnosed by the site investigator only on noncontrast computed tomography scan secondary to anterior circulation large-vessel occlusion up to 24 hours from stroke symptoms onset.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".