Review of Current Large Core Volume Stroke Thrombectomy Clinical Trials: Controversies and Progress
Bibliographic record
Abstract
Large clinical trials have helped establish the benefit of endovascular treatment (EVT) in patients with acute ischemic stroke with large vessel occlusion and small infarct core volume as determined by scores ≥6 on the Alberta Stroke Program Early CT Scores. Several small studies have suggested that patients with large infarct core volume (LICV) may also benefit from EVT. Currently, at least 6 randomized clinical trials are examining the benefit of extending EVT to this population of patients with acute ischemic stroke. These trials were independently conceived and have significant differences in their inclusion criteria. Understanding these inclusion criteria and other differences in trial design is pivotal for the field to interpret the upcoming results of these trials. In this review, the designs of the 6 trials are summarized and compared. Specific differences are described, including (1) the rationale for EVT treatment in patients with LICV, (2) how to define LICV and the imaging modality used to identify LICV, (3) inclusion of an Alberta Stroke Program Early CT Score 0 to 5 versus 3 to 5, (4) use of the mismatch between blood flow and the size of infarct as an inclusion criterion, and (5) inclusion of early window and/or late window patients. The potential impact of these trial results on current guidelines for acute ischemic stroke is discussed. Differences in trial design as well as inclusion and exclusion criteria may influence trial outcomes. The implications of these trial results will likely be enhanced by a pooled analysis.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".