Abstract TP60: Intravenous Thrombolysis For Patients With Reverse MRA-DWI Mismatch: SAMURAI And NCVC Rt-PA Registries
Bibliographic record
Abstract
Background and purpose: Characteristics of reverse MRA-DWI mismatch, defined as large DWI lesion despite absence of the major artery occlusion (MAO), remain unknown, especially in patients treated with IV rt-PA. This study aimed to clarify the frequency, associated factors, and outcomes of patients showing reverse MRA-DWI mismatch prior to IV rt-PA therapy. Methods: From the multicenter (SAMURAI) and additional single-center (NCVC) rt-PA registries, patients with the MCA territorial stroke were included. Early ischemic changes (EIC) were assessed with the Alberta Stroke Program Early CT score (ASPECTS) on pretreatment DWI. MAO was defined as ICA or M1 occlusion on MRA. Patients were divided into 4 groups: the large-EIC match (LM) group (MAO, ASPECTS <7); the reverse mismatch (RMM) group (no MAO, ASPECTS <7); the conventional mismatch (CMM) group (MAO, ASPECTS ≧7); and the small-EIC match (SM) group (no MAO, ASPECTS ≧7). Outcomes included sICH per ECASS II criteria, and mRS 0-2 and death at 90 days. Multivariate backward stepwise logistic regression analysis was performed to identify independent clinical characteristics (demographic factors, risk factors, stroke subtypes by TOAST classification, and blood tests) associated with the reverse MRA-DWI mismatch and to compare the outcomes among the 4 groups. Results: Of the 486 patients (167 women, median age 74 years) enrolled, reverse MRA-DWI mismatch was observed in 24 (5%, RMM group); 108 belonged to LM, 161 to CMM, and 193 to SM groups. Among clinical characteristics, cardioembolism (RMM 92%, LM 76%, CM 69%, SM 49%) was only independently associated with the RMM group (OR 5.49, 95%CI 1.25-24.1). Median initial NIHSS score was 18 in RMM, 18 in LM, 13 in CMM, and 8 in SM (p<0.001). MRS 0-2 (RMM 54%, LM 19%, CMM 46%, SM 69%) was more common in the RMM than the LM group (OR 4.02, 95% CI 1.28-12.7). SICH (RMM 13%, LM 6%, CMM 2%, SM 2%) and death (RMM 8%, LM 12%, CMM 9%, SM 2%) were not different between the RMM and LM groups after multivariate analysis. Conclusion: Reverse MRA-DWI mismatch was observed in 5% of patients eligible for rt-PA. Cardioembolism was independently associated with reverse mismatch. Patients with reverse mismatch may benefit from thrombolysis, compared to those with extensive EIC with MAO.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".