A Comparison of Mechanical Thrombectomy in the M1 and M2 Segments of the Middle Cerebral Artery: A Review of 585 Consecutive Patients
Bibliographic record
Abstract
Background: Mechanical thrombectomy for anterior-circulation large-vessel occlusion has shown benefit; however, the question of whether this technique is safe and effective in the distal vasculature remains unanswered. We sought to compare the outcome data from mechanical thrombectomy of the M2 branches of the middle cerebral artery (MCA) with those of the M1 segment. Methods: We performed a retrospective analysis of prospectively collected data of patients with acute ischaemic stroke undergoing mechanical thrombectomy of isolated M1 or M2 branches of the MCA between August 2008 and August 2016. Results: We identified 585 patients, 479 with M1 occlusions and 106 with M2 occlusions. The average age was 72 ± 12.8 and 68 ± 13.8 years, respectively (p = 0.007). The baseline Alberta Stroke Program Early Computed Tomographic (ASPECT) score was similar in both cohorts, but patients with M1 occlusions presented with higher mean National Institutes of Health Stroke Scale (NIHSS) scores of 15.7 compared to 11.8 (p < 0.001). There was no significant difference in the average procedure time for each cohort; fewer thrombectomy attempts were required in the M2 cohort (2.3 vs. 1.8, p = 0.0004), but the overall time to recanalization was longer in the M2 cohort (353 vs. 399 min, p < 0.001). Similar rates of successful reperfusion (Thrombolysis in Ischaemic Stroke score [TICI] ≥2b 88.5 vs. 90.5%, p = 0.612) were seen, but food outcome (modified Rankin Scale ≤2) was lower in M1 occlusions (37.2 vs. 54.3%, p < 0.001). Rates of symptomatic intracranial haemorrhage were similar. Conclusion: Good clinical outcomes can be achieved for both groups with no significant differences in procedure length, final TICI recanalization rates or intracranial haemorrhage between the M1 and M2 cohorts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".