Efficacy and safety of mechanical thrombectomy in distal medium middle cerebral artery occlusion ischemic stroke patients on low-dose aspirin
Bibliographic record
Abstract
BACKGROUND: Acute ischemic stroke (AIS) from distal medium vessel occlusion (DMVO) presents unique treatment challenges. Mechanical thrombectomy (MT) is emerging as a viable option for these patients, yet the role of pre-stroke aspirin treatment is unclear. This study evaluates the impact of pre-stroke low-dose aspirin on outcomes in DMVO patients undergoing MT. METHODS: We conducted a multinational, multicenter, propensity score-weighted analysis within the Multicenter Analysis of primary Distal medium vessel occlusions: effect of Mechanical Thrombectomy (MAD-MT) registry. Patients with AIS due to DMVO, treated with MT, were included. We compared outcomes between patients on pre-stroke low-dose aspirin (75-100 mg) and those not on antiplatelet therapy. The primary outcome was functional independence at 90 days (modified Rankin Scale (mRS), 0-2). Secondary outcomes included excellent functional outcome at 90 days (mRS, 0-1), mortality, and day 1 post-MT National Institutes of Health Stroke Scale (NIHSS) score. Safety outcomes focused on hemorrhagic complications, including symptomatic intracerebral hemorrhage (sICH). RESULTS: Among 1354 patients, 150 were on pre-stroke low-dose aspirin. After applying inverse probability of treatment weighting (IPTW), aspirin use was associated with significantly better functional outcomes (mRS, 0-2: odds ratio (OR) = 1.89, 95% confidence interval (CI) = 1.14 to 3.12) and lower 90-day mortality (OR = 0.56, 95% CI = 0.32 to 1.00). The aspirin group had lower NIHSS scores on day 1 (β = -1.5, 95% CI = -2.8 to -0.27). The sICH rate was not significantly different between the groups (OR = 0.92, 95% CI = 0.60 to 1.43). CONCLUSIONS: Pre-stroke low-dose aspirin was associated with improved functional outcomes and reduced mortality in patients with DMVO undergoing MT, without a significant increase in sICH. These findings suggest that low-dose aspirin may be safe and associated with more frequent excellent outcomes for this patient population. Further prospective studies are needed to validate these results and assess long-term outcomes.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".