Penumbra salvage in extensive stroke: exploring limits for reperfusion therapy
Bibliographic record
Abstract
BACKGROUND: The effect of thrombectomy in patients presenting with extensive ischemic stroke at baseline is currently being investigated; it remains uncertain to what extent brain tissue may be saved by reperfusion in such patients. Penumbra salvage volume (PSV) has been described as a tool to measure the volume of rescued penumbra. OBJECTIVE: To assess whether the effect of recanalization on PSV is dependent on the extent of early ischemic changes. METHODS: Observational study of patients with anterior circulation ischemic stroke triaged by multimodal-CT undergoing thrombectomy. PSV was defined as the difference between baseline penumbra volume and net infarct growth to follow-up. The effect of vessel recanalization on PSV depending on the extent of early ischemic changes (defined using Alberta Stroke Program Early CT Score (ASPECTS) and core volumes based on relative cerebral blood flow) was determined using multivariable linear regression analysis, and the association with functional outcome at day 90 was tested using multivariable logistic regression. RESULTS: 384 patients were included, of whom 292 (76%) achieved successful recanalization (modified Thrombolysis in Cerebral Infarction ≥2b). Successful recanalization was independently associated with 59 mL PSV (95% CI 29.8 to 88.8 mL) and was linked to increased penumbra salvage up to an ASPECTS of 3 and core volume up to 110 mL. Recanalization was associated with a higher probability of a modified Rankin Scale score of ≤2 up to a core volume of 100 mL. CONCLUSIONS: Recanalization was associated with significant penumbra salvage up to a lower ASPECTS margin of 3 and upper core volume margin of 110 mL. The clinical benefit of recanalization for patients with very large ischemic regions of >100 mL or ASPECTS <3 remains uncertain and requires prospective investigation.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".