Endovascular therapy versus best medical management in distal medium middle cerebral artery acute ischaemic stroke: a multinational multicentre propensity score-matched study
Bibliographic record
Abstract
BACKGROUND: The efficacy of endovascular treatment (EVT) in acute ischaemic stroke due to distal medium vessel occlusion (DMVO) remains uncertain. Our study aimed to evaluate the safety and efficacy of EVT compared with the best medical management (BMM) in DMVO. METHODS: In this prospectively collected, retrospectively reviewed, multicentre cohort study, we analysed data from the Multicentre Analysis of primary Distal medium vessel occlusions: effect of Mechanical Thrombectomy registry. Patients with acute ischaemic stroke due to DMVO in the M2, M3 and M4 segments who underwent EVT or received BMM were included. Primary outcome measures comprised 10 co-primary endpoints, including functional independence (mRS 0-2), excellent outcome (mRS 0-1), mortality (mRS 6) and haemorrhagic complications. Propensity score matching was employed to balance the cohorts. RESULTS: Among 2125 patients included in the primary analysis, 1713 received EVT and 412 received BMM. After propensity score matching, each group comprised 391 patients. At 90 days, no significant difference was observed in achieving mRS 0-2 between EVT and BMM (adjusted OR 1.00, 95% CI 0.67 to 1.50, p>0.99). However, EVT was associated with higher rates of symptomatic intracerebral haemorrhage (8.4% vs 3.0%, adjusted OR 3.56, 95% CI 1.69 to 7.48, p<0.001) and any intracranial haemorrhage (37% vs 19%, adjusted OR 2.61, 95% CI 1.81 to 3.78, p<0.001). Mortality rates were similar between groups (13% in both, adjusted OR 1.48, 95% CI 0.87 to 2.51, p=0.15). CONCLUSION: Our findings suggest that while EVT does not significantly improve functional outcomes compared with BMM in DMVO, it is associated with higher risks of haemorrhagic complications. These results support a cautious approach to the use of EVT in DMVO and highlight the need for further prospective randomised trials to refine treatment strategies.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".