ERASER
Bibliographic record
Abstract
Background and Purpose- Using a novel study design with virtual comparators based on predictive modeling, we investigated whether next-generation mechanical thrombectomy devices improve outcomes in patients with ischemic stroke. We hypothesized that this new study design shows that a next-generation mechanical thrombectomy system is superior to intravenous tPA (tissue-type plasminogen activator) therapy (IVT) alone. Methods- ERASER (Eric Acute Stroke Recanalization) was an investigator-initiated, prospective, multicenter, single-arm (virtual 2-arm) study that evaluated the effectiveness of a new recanalization device together with a specific intermediate catheter (Embolus Retriever with Interlinked Cages/SOFIA, Microvention) in stroke patients with internal carotid artery or middle cerebral artery occlusions. The primary end point was the volume of saved tissue. Volume of saved tissue was defined as the difference of actual infarct volume and brain volume predicted to develop infarction using a machine learning model based on data from intravenous tPA therapy patients. Results- Eighty-one patients were enrolled. The median patient age was 71 years (interquartile range, 61-77). National Institutes of Health Stroke Scale score was 14 (interquartile range, 12-18). The actual infarct volume was smaller than predicted by the intravenous tPA therapy model, with a median volume of saved tissue of 50 mL (interquartile range, 19-103; P<0.0001). Good clinical outcome (modified Rankin Scale, 0-2 at 90 days) was observed in 48 out of 69 (70%). The recanalization rate (Thrombolysis in Cerebral Infarction 2b/3) was 95%. Conclusions- ERASER is the first mechanical thrombectomy study with a primary end point based on predictive analytics enabling intraindividual virtual comparisons. The next-generation mechanical thrombectomy method resulted in smaller infarcts than predicted after intravenous tPA therapy alone and showed a high rate of good clinical outcome. The novel study design with virtual comparisons is promising for further application and testing in the neurovascular arena. Clinical Trial Registration- URL: https://www.clinicaltrials.gov . Unique identifier: NCT02534701.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.510 | 0.351 |
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".