Clinical outcomes of patients with unsuccessful mechanical thrombectomy versus best medical management of medium vessel occlusion stroke in the middle cerebral artery territory
Bibliographic record
Abstract
BACKGROUND: Current randomized controlled trials are investigating the efficacy and safety of mechanical thrombectomy (MT) in patients with medium vessel occlusion (MeVO) stroke. Whether best medical management (MM) is more efficient than unsuccessful vessel recanalization during MT remains unknown. METHODS: This was a retrospective cohort study using data from 37 academic centers across North America, Asia, and Europe between September 2017 and July 2021. Only patients with occlusion of the distal branches (M2 and M3) of the middle cerebral artery territory were included. Unsuccessful MT was defined as a modified Thrombolysis in Cerebral Infarction score of 0-2a. Propensity score matching was used to control for confounders. The primary outcome was functional independence, defined as a modified Rankin Scale (mRS) score of 0-2 at 90 days after treatment. Multivariable regression analysis was used to assess factors associated with the primary outcome. RESULTS: Of 2903 patients screened for eligibility, 532 patients were analyzed (266 per group) after propensity score matching. The MM group had superior functional outcomes, with 32% achieving mRS 0-1 at 90 days compared with 21% in the MT group (P=0.011). Patients in the MM group also had significantly lower rates of symptomatic intracranial hemorrhage (sICH) (3.4% vs 16%, P<0.001) and any hemorrhage (18% vs 48%, P<0.001). On multivariable regression, unsuccessful MT was associated with reduced odds of functional independence (OR 0.50, 95% CI 0.29 to 0.85, P=0.011) and increased odds of sICH (OR 4.32, 95% CI 1.84 to 10.10, P<0.001). Mortality rates were similar between groups (27% in MM vs 29% in MT, P=0.73). CONCLUSION: Unsuccessful MT for MeVO was linked to worse outcomes than best MM. These findings highlight the risks of prolonged attempts and emphasize the importance of efficient procedural decision-making to reduce complications and improve patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".