Endovascular therapy versus medical management in isolated posterior cerebral artery acute ischemic stroke: A multinational multicenter propensity score-weighted study
Bibliographic record
Abstract
Abstract Background: Despite the proven effectiveness of endovascular therapy (EVT) in acute ischemic strokes (AIS) involving anterior circulation large vessel occlusions, isolated posterior cerebral artery (PCA) occlusions (iPCAo) remain underexplored in clinical trials. This study investigates the comparative effectiveness and safety of EVT against medical management (MM) in patients with iPCAo. Methods: This multinational, multicenter propensity score-weighted study analyzed data from the Multicenter Analysis of primary Distal medium vessel occlusions: effect of Mechanical Thrombectomy (MAD-MT) registry, involving 37 centers across North America, Asia, and Europe. We included iPCAo patients treated with either EVT or MM. The primary outcome was the modified Rankin Scale (mRS) at 90 days, with secondary outcomes including functional independence, mortality, and safety profiles such as hemorrhagic complications. Results: A total of 177 patients were analyzed (88 MM and 89 EVT). EVT showed a statistically significant improvement in 90-day mRS scores (OR = 0.55, 95% CI = 0.30–1.00, p = 0.048), functional independence (OR = 2.52, 95% CI = 1.02–6.20, p = 0.045), and a reduction in 90-day mortality (OR = 0.12, 95% CI = 0.03–0.54, p = 0.006) compared to MM. Hemorrhagic complications were not significantly different between the groups. Conclusion: EVT for iPCAo is associated with better neurological outcomes and lower mortality compared to MM, without an increased risk of hemorrhagic complications. Nevertheless, these results should be interpreted with caution due to the study’s observational design. The findings are hypothesis-generating and highlight the need for future randomized controlled trials to confirm these observations and establish definitive treatment guidelines for this patient population.
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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 | 0.007 |
| 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 | 0.000 | 0.001 |
| 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".