Abstract W P56: Using The M2 Vessel Diameter And Baseline NIHSS To Identify Which M2 Occlusions Should Be Treated Endovascularly?
Bibliographic record
Abstract
Introduction: IV tPA is the primary acute treatment for M2 occlusions yet outcomes and recanalization rates are less than optimal. Endovascular treatment may be a more suitable treatment option in some but not all M2 occlusions yet are excluded from most current endovascular trials. Current methodologies to characterize M2s are complex and quite subjective. A simple and practical approach to evaluating M2s quickly for endovascular treatment is needed. We measured M2 cross-sectional diameter to determine if this method predicted 24-hour infarct volumes. Methods: Patients from the ongoing prospective multicenter INTERRSECT recanalization study with an M2 occlusion identified by baseline CTA were included. Two readers measured M2 diameter on baseline CTA at the most distal point of normal vessel upstream to the clot by consensus. Recanalization (modified AOL score 2-3) was assessed on 4 hour follow-up CTA. Infarct volume was measured on 24 hr CT/MRI. Results: 103 patients (mean age 74.1 yrs, SD=12.7; 46.5% male; median baseline NIHSS 8, IQR=7) had M2 occlusion on baseline CTA. 76/103 received IV t-PA. Recanalization was noted in 46/92 (50%) patients. Median 24-hr infarct volume was 4.28 ml (IQR=22.67 ml). In multivariable linear regression, M2 diameter (p<0.01) and baseline NIHSS (p=0.01) were associated with final infarct volume but not recanalization (p=53). Median final infarct volume was 41.6 ml (IQR=50.4) in patients with M2 diameter>2mm and baseline NIHSS>5 vs < 10 ml in all the other 3 groups (p<0.01; equality of medians test; see figure). Conclusion: Patients with M2 diameter > 2 mm just proximal to the occlusion and baseline NIHSS > 5 have much higher final infarct volumes suggesting a role for ultra-early recanalization that is offered by endovascular treatment. Such patients could be selected for endovascular therapy in future trials or clinical practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".