Efficacy of endovascular thrombectomy in patients with M2 segment middle cerebral artery occlusions: meta-analysis of data from the HERMES Collaboration
Bibliographic record
Abstract
BACKGROUND: The Society of Neurointerventional Surgery revised its operational definition of emergent large vessel occlusion (ELVO) recently to include proximal M2 segment middle cerebral artery (MCA) occlusions. We sought to assess the benefit of endovascular thrombectomy (EVT) over best medical care for M2 segment MCA occlusion. METHODS: Patient level data from trials in the HERMES Collaboration were included. The HERMES core laboratory identified patients with M2 segment MCA occlusions and further classified them as proximal versus distal, anterior versus posterior division, and dominant versus co-dominant versus non-dominant. Primary outcome was modified Rankin Scale (mRS) score 0-2 at 90 days. Secondary outcomes were modified Thrombolysis in Cerebral Infarction (mTICI) rates at end of procedure, 90-day mRS shift, 90-day mRS 0-1, 24 hours National Institute of Health Stroke Scale (NIHSS) score 0-2, symptomatic intracerebral hemorrhage (ICH), and death. RESULTS: 130 patients with M2 MCA (proximal location n=116 vs distal n=14, anterior division n=72 vs posterior n=58, dominant n=73 vs co-dominant n=50 vs non-dominant n=7) were included. Successful reperfusion (mTICI 2b or 3) among those undergoing EVT was seen in 59.2% of patients. Treatment effect favored EVT (adjusted OR 2.39, 95% CI 1.08 to 5.28, p=0.03) for 90-day mRS 0-2 (58.2% EVT vs 39.7% control). Direction of benefit favored EVT for other outcomes. Treatment effect favoring EVT was maximal in patients with proximal M2 segment MCA occlusions (n=116, adjusted OR 2.68, 95% CI 1.13 to 6.37) and in dominant M2 segment MCA occlusions (n=73, adjusted OR 4.08, 95% CI 1.08 to 15.48). No sICH (0%) was observed in patients treated with EVT compared with five (7.9%) in the control arm. CONCLUSION: Patients with proximal M2 segment MCA occlusions eligible for EVT trial protocols benefited from EVT.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.036 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".