Acute Basilar Artery Occlusion Thrombectomy Performed in Early (<6 hours) and Late Time Window (>6 hours) from the PC-SEARCH Registry (S24.002)
Bibliographic record
Abstract
Objective: Evaluate the effect of early and late time window in a cohort of patients with BAO treated with thrombectomy. Background: Acute Basilar Artery Occlusion (BAO) results in high rate of morbidity and mortality. Recent randomized controlled trials from China demonstrated clinical benefit of mechanical thrombectomy. Design/Methods: PC-SEARCH is a large multi-centered retrospective registry of consecutive acute BAOs treated with thrombectomy with contributions from eight high-volume centers across the United States from July 2015 – December 2021. Patients were included in this registry if they received mechanical thrombectomy or intra-arterial thrombolysis within 24 hours of last seen normal. Registry includes data from baseline characteristics, pre- and intra- procedural data, radiographic and clinical outcomes. Good clinical outcomes were defined as mRS ≤ 3. Times were dichotomized into early (< 6 hours) and late (> 6 hours) time windows. Multivariate logical regression models were used to evaluate predictors of good outcome. Results: PC-SEARCH registry captured 519 patients, 479 with recorded outcomes at 90 days, Mean last-seen-normal to groin-puncture time was 132 min in the early time window and 765 min in the late time window patients; while NIHSS ( 17 vs 16, p 0.057), age (mean 65.8 vs 67.4, p 0.175), PC-ASPECTS (median 10 vs 9, p value 0.45), and door-groin puncture time (295 min vs 389 p 0.28) were not different between the two groups. Good recanalization (≥TICI 2b) was achieved in 82% of patients in the early time window and 81.5 % in the late time window (p 0.45). Rate of good outcome (45.8 vs 41.8, p value 0.41), sICH (7.1 vs 6.8 p 0.897) and mortality (40.3 vs 43.4 p 0.869) were similar between cohorts. Conclusions: In patients with acute basilar artery occlusion with excellent PC ASPECT score, similar rates of good clinical outcome can be achieved in the early and late time window. Disclosure: Dr. Aladamat has nothing to disclose. Dr. Mierzwa has nothing to disclose. Dr. Zaidi has nothing to disclose. Dr. Gharaibeh has nothing to disclose. Dr. Afreen has nothing to disclose. Sami Al Kasab has nothing to disclose. Dr. Nelson has nothing to disclose. Dr. Farooqui has nothing to disclose. Mr. Vivanco-Suarez has nothing to disclose. Dr. Jadhav has nothing to disclose. Dr. Desai has nothing to disclose. Dr. Toth has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Dynamed. Dr. Toth has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Microvention. Dr. Toth has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Medtronic. Dr. Alrohimi has nothing to disclose. Dr. Nguyen has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Vesalio. Dr. Nguyen has received personal compensation in the range of $0-$499 for serving on a Scientific Advisory or Data Safety Monitoring board for NIH. Dr. Nguyen has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Avania. Dr. Nguyen has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for AHA. The institution of Dr. Nguyen has received research support from Boston Medical Center. The institution of Dr. Nguyen has received research support from Society of Vascular and Interventional Neurology. Mr. Klein has nothing to disclose. Mohamad Abdalkader has nothing to disclose. Dr. Pandey has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for NIH and SVIN- Journal. Dr. Pandey has stock in FlexDex. Dr. Pandey has stock in NextGen. The institution of Dr. Pandey has received research support from NIH. The institution of Dr. Pandey has received research support from Focused ultrasound foundation. Dr. Pandey has received intellectual property interests from a discovery or technology relating to health care. Sravanthi Koduri has nothing to disclose. Nirav Vora has nothing to disclose. Vora Shivangi has nothing to disclose. Dr. Jumaa has nothing to disclose. Dr. Ortega Gutierrez has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for stryker. Dr. Ortega Gutierrez has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for medtronic. Dr. Ortega Gutierrez has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for microvention. Dr. Ortega Gutierrez has received personal compensation in the range of $0-$499 for serving as an officer or member of the Board of Directors for SVIN. The institution of Dr. Ortega Gutierrez has received research support from stryker. The institution of Dr. Ortega Gutierrez has received research support from Siemens. The institution of Dr. Ortega Gutierrez has received research support from IschemiaView. The institution of Dr. Ortega Gutierrez has received research support from Medtronic.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".