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Record W4391438029 · doi:10.1161/str.55.suppl_1.tp200

Abstract TP200: Anticoagulation Use and Endovascular Thrombectomy in Patients With Large Core Stroke - A Secondary Analysis of SELECT2 Trial

2024· article· en· W4391438029 on OpenAlexaff
Deep Pujara, Faris Shaker, Michael Abraham, Michael Chen, Scott E. Kasner, Santiago Ortega‐Gutiérrez, MS Hussain, Leonid Churilov, Sophia Sundararajan, Yin Hu, Michael A. De Georgia, Amanda Opaskar, Faisal Al-Shaibi, Rami Moussa, Mohammad A Abdulrazzak, Hannah Johns, Cathy A. Sila, Anthony J. Furlan, Vítor Mendes Pereira, Michael D. Hill, James C. Grotta, Marc Ribó, Ameer E Hassan, Bruce Campbell, Amrou Sarraj

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of CalgaryToronto Western Hospital
Fundersnot available
KeywordsMedicineStroke (engine)Endovascular treatmentSurgeryAneurysm

Abstract

fetched live from OpenAlex

Introduction: Anticoagulation (AC) use is common in patients presenting with acute ischemic stroke and is known to pose challenges to acute reperfusion therapy. However, evidence about association of AC use prior to stroke with endovascular thrombectomy outcomes and post-procedure hemorrhages, especially in those with large strokes is limited. Methods: From SELECT2, patients were stratified based on AC medication use and prior to stroke. Functional outcomes at 90day follow-up and hemorrhagic transformation on follow-up imaging were compared between patients with and without AC in adjusted regression models. Results: Of 352 patients, 29/180 (16%, VKA - 15, DOACs 14) EVT patients and 18/172 (10%, VKA - 3, DOACs 15) MM patients were receiving anticoagulants at baseline. AC patients were older (72 (62-79) y vs 66 (58-75) y), with higher cardiac morbidity (Congestive Heart Failure: 28% vs 10%, Atrial Fibrillation: 70% vs 17%), but had similar NIHSS [20 (16-24) vs 18 (15-23)], time to randomization [511 (350-909) vs 586 (326-920) minutes], CT ASPECTS [4 (3-5) vs 4 (3-5)] and ischemic core estimates [91 (71 -110) vs 103 (71-139) ml, AC vs nonAC respectively]. Within AC patients, EVT did not improve outcomes (Shift: 6 (4-6) vs 5 (4-6), aGenOR: 0.89 (0.53-1.50), mRS 0-3: 11% vs 14%, aRR: 1.27 (0.40-4.05), mRS 5-6: 69% vs 67%, aRR: 1.05 (0.73-1.50)]. Furthermore, EVT patients on AC reported numerically higher rates of any intracerebral hemorrhage [85.7% vs 70.2%, aRR: 1.18, 95% CI: 0.98-1.43], but no sICH or parenchymal hemorrhage and demonstrated worse outcome [median mRS: 6 (4-6) vs 4 (3-6), aGenOR: 0.49(0.32-0.74)], mRS 0-3: 14% vs 43%, aRR: 0.36 (0.15-0.86)], and mRS 5-6: 69% vs 43%, aRR: at 90 day follow-up and numerically lower functional independence (mRS 0-2) [3.4% vs 23.3%, aRR: 0.18(0.03-1.21)], AC vs nonAC respectively. Consistent results were observed in patients achieving successful reperfusion. Conclusion: Almost 1/7 th of patients presenting with large stroke in SELECT2 trial demonstrated AC use at baseline, with higher cardiac morbidity. These patients were more likely to have hemorrhagic outcomes and worse clinical outcomes after EVT and successful reperfusion. Clinicaltrials.gov registration: NCT03876457

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.016
GPT teacher head0.263
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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