The Large Core Paradox
Bibliographic record
Abstract
Recently, 6 randomized controlled trials of endovascular treatment (EVT) versus medical management in anterior circulation large vessel occlusion with large-core documented significant benefit of EVT on functional outcome. Moreover, one trial reported the benefit of EVT in the very large-core category (Alberta Stroke Program Early CT Score, 0-2). These results are considered paradoxical by some as they contradict the prevailing view that the presence of a large core precludes the possibility of good outcomes following reperfusion. They, in turn, led some investigators to question the applicability of the core/penumbra model in the case of large-core stroke and even its overall validity, specifically regarding the notion that the core reliably predicts tissue infarction. Here, we discuss the trial results and propose alternative explanations for the large-core paradox. First, although EVT does improve outcomes as compared with medical management, overall outcomes remain poor in ≈80% of the treated population. Second, the assessment of core extent on imaging, particularly with computed tomography, is potentially inaccurate, especially in the early time window. Third, consistent with observational studies, some randomized controlled trial substudies suggest that the benefit of EVT in this population derives at least in part from the salvage of penumbra, which appears to have been present in a large percentage of enrolled patients. Fourth, the markedly reduced perfusion that prevails within large cores facilitates the early development of vasogenic edema. This heterogeneity of tissue injury may, in turn, lead to an overestimation of true core/neuronal death as estimated with computed tomography and magnetic resonance imaging. Assessing patients with apparent large core should consider these notions when discussing eligibility for EVT. Early reperfusion of large-core patients is expected to both target any residual penumbra and prevent the development of vasogenic edema within the severely hypoperfused areas. These considerations underscore the need for more reliable methods to identify irreversible neuronal injury inside the imaging-based estimated core.
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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 | 0.036 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".