Association of Reperfusion and Procedural Characteristics with Endovascular Thrombectomy Outcomes in Large Core Stroke: Sub‐Analysis from the <scp>SELECT2</scp> Trial
Bibliographic record
Abstract
Endovascular thrombectomy (EVT) was shown to be safe and efficacious in patients with large core stroke in multiple randomized controlled trials. However, the impact of reperfusion and other procedural metrics on EVT outcomes in this population has not been well-characterized. METHODS: From the SELECT2 trial, we evaluated the association between reperfusion status, first-pass effect (near-complete or complete reperfusion [extended thrombolysis in cerebral infarction (eTICI) 2c-3] in 1 pass), procedure time and primary technique (aspiration vs stent-retriever) with functional outcomes in patients receiving EVT across ASPECTS (3 vs 4 vs 5) and core estimate strata (<70 vs ≥70ml, <100 vs ≥100ml, and <150 vs ≥150ml). RESULTS: Of 180 patients who received thrombectomy, 144 (80%) achieved successful reperfusion (eTICI 2b-3) and demonstrated better clinical outcomes (adjusted generalized odds ratios [aGenOR]: 1.48, 95% confidence interval [CI]: 1.01-2.15), compared with unsuccessful reperfusion. Results were consistent across ASPECTS and core estimate strata. Additionally, complete or near-complete reperfusion (eTICI 2c-3) was associated with better functional outcome (aGenOR: 1.99, 95% CI: 1.33-2.97) in patients achieving successful reperfusion. Functional outcome point estimates favored those with first-pass-effect (42 of 167 (25%), aGenOR: 1.46, 95% CI: 0.96-2.24). Longer procedure time was associated with worse modified Rankin scale (mRS) distribution (aGenOR: 0.92, 95% CI: 0.87-0.96, p-value = 0.001 for 10 minutes increment). Aspiration-first technique was used in 43 of 154 (25%) patients and was not associated with higher reperfusion (88% vs 78%, p = 0.18) or better functional outcome (aGenOR: 0.74, 95% CI: 0.50-1.10) as compared with stent-retriever first. INTERPRETATION: Successful reperfusion resulted in improved clinical outcomes in large core patients across baseline ischemic core strata. Near complete or complete reperfusion was further associated with better outcomes, whereas prolonged procedures were associated with worse outcomes. Results were consistent regardless of the technique used. ANN NEUROL 2024.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".