B.1 CT Or MRI protocol for acute stroke reperfusion with EVT (COMPARE): an international retrospective cohort study
Bibliographic record
Abstract
Background: Patients with an acute ischemic stroke (AIS) are selected to receive reperfusion therapy using either computed tomography (CT-CTA) or magnetic brain imaging (MRI). The aim of this study was to compare CT and MRI as the primary imaging modality for AIS patients undergoing EVT. Methods: Data for AIS patients between January 2018 and January 2021 were extracted from two prospective multicenter EVT cohorts: the ETIS registry in France (MRI) and the OPTIMISE registry in Canada (CT). Demographics, procedural data and outcomes were collected. We assessed the association of qualifying imaging (CT vs. MRI) with time metrics and functional outcome. Results: From January 2018 to January 2021, 4059 patients selected by MRI and 1324 patients selected by CT were included in the study. Demographics were similar between the two groups. The median imaging-to-arterial puncture time was 37 minutes longer in the MRI group. Patients selected by CT had more favorable 90-day functional outcomes (mRS 0-2) as compared to patients selected by MRI (48.5% vs 44.4%; adjusted OR (aOR), 1.54, 95%CI 1.31 to 1.80, p<0.001). Conclusions: Patients with AIS undergoing EVT who were selected with MRI as opposed to CT had longer imaging-to-arterial-puncture delays and worse functional outcomes at 90 days.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".