First-Pass Effect Predicts Clinical Outcome and Infarct Growth After Thrombectomy for Distal Medium Vessel Occlusions
Bibliographic record
Abstract
BACKGROUND: The first-pass effect in endovascular thrombectomy (EVT) has been associated with better clinical outcomes and decreased stroke progression in large vessel occlusion but has not been evaluated in distal, medium vessel occlusions (DMVOs). OBJECTIVE: To assess the impact on clinical outcome and stroke progression of the modified first-pass effect (defined as a successful first-pass [modified Thrombolysis In Cerebral Infarction 2b/2c/3] revascularization) in patients who underwent EVT for a primary DMVOs. METHODS: We collected data from consecutive patients who underwent EVT for a primary DMVO at a single large academic center. We compared the rate of good clinical outcome (modified Rankin Scale of 0-2 at 3 months) and stroke progression between patients who demonstrated modified first-pass effect (mFPE) vs those who did not (no-mFPE). RESULTS: Between January 2018 and January 2021, we included 60 patients who underwent EVT for an acute ischemic stroke with a primary DMVO. Overall, mFPE was achieved in 32% (19/60) of EVTs. The mFPE was associated with a higher rate of good clinical outcome compared with no-mFPE (89% vs 46%, odds ratio = 16.04 [2.23-115.39], P = .006 in multivariate analysis). Final stroke volume was less among mFPE patients (6.9 mL [4.7-13.6] vs 23 mL [14.6-47], P = .001) as was stroke progression (6.8 mL [4-12.1] vs 17.8 mL [8.1-34.9], P = .016). The mFPE was still associated with higher rates of good clinical outcome when compared with patients reaching an modified Thrombolysis In Cerebral Infarction score ≥2b in more than 1 pass (89% vs 53%; odds ratio = 7.37 [1.43-38.08], P = .017). CONCLUSION: The mFPE may be associated with better clinical outcomes and lower stroke progression in DMVO.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".