First pass effect in patients with large core infarcts undergoing mechanical thrombectomy: subgroup analysis of the prospective international ASSIST registry
Bibliographic record
Abstract
BACKGROUND: Studies have described a first pass effect (FPE) where patients with successful recanalization after one pass experience better outcomes. Few studies have evaluated this in patients with large core infarctions. OBJECTIVE: To determine whether patients with large core infarcts undergoing mechanical thrombectomy in which first pass reperfusion is achieved experience improved outcomes compared with those who undergo more than one pass. METHODS: The ASSIST Registry, a prospective, global, multicenter registry of patients with anterior circulation large vessel occlusion (LVO) undergoing mechanical thrombectomy was used. Adults with internal carotid artery/M1/M2 occlusions and preprocedural Alberta Stroke Program Early CT Score (ASPECTS) <6 were included. The variable of interest was number of thrombectomy passes (dichotomized to 1 or >1) performed for the target occlusion. The primary outcome was 90-day good functional outcome defined as modified Rankin Scale (mRS) score 0-3. RESULTS: 150 patients with a mean age of 66 years were included. Most patients had ASPECTS of 4 (33%) or 5 (59%). 77 patients (51%) underwent one pass. Compared with patients with one pass, those with more than one pass had significantly lower odds of good functional outcome (OR=0.44, 95% CI 0.21 to 0.93; P=0.03). More than one pass was not significantly associated with 90-day mRS score 0-2 (OR=0.46, 95% CI 0.15 to 1.43; P=0.17) or mortality (OR=2.03, 95% CI 0.81 to 5.08; P=0.13). FPE (one pass eTICI≥2c) and modified FPE (one pass extended thrombolysis in cerebral infarction ≥2b50) were not significantly associated with 90-day mRS 0-3, mortality, or symptomatic intracranial hemorrhage. CONCLUSION: This analysis suggests that use of multiple passes is associated with worse outcomes in patients with large core infarcts.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".