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Record W4309300748 · doi:10.1161/svin.122.000642

Basilar Artery Occlusion Thrombectomy Technique: An International Survey of Practice Patterns

2022· article· en· W4309300748 on OpenAlexaff
Piers Klein, Ana Herning, Brian Drumm, Jean Raymond, Mohamad Abdalkader, James E. Siegler, Yimin Chen, Xiaochuan Huo, Wouter J. Schonewille, Xinfeng Liu, Wei Hu, Xunming Ji, Bertrand Lapergue, Chuanhui Li, Fana Alemseged, Daniel Strbian, Urs Fischer, Johannes Kaesmacher, Hiroshi Yamagami, Volker Puetz, Simona Sacco, Espen Saxhaug Kristoffersen, Jelle Demeestere, Kyriakos Lobotesis, Dylan Roi, Kubilay Aydın, Francesco Diana, Hesham Masoud, Alice Ma, Roberta Novakovic‐White, Fawaz Al‐Mufti, Yuyou Zhu, Hongfei Sang, Dapeng Sun, Thang Huy Nguyen, Jean‐Christophe Gentric, Jildaz Caroff, Marios‐Nikos Psychogios, Arturo Consoli, Lukas Meyer, Jens Fiehler, Joey English, Rishi Gupta, Bernard Yan, Bruce Campbell, Ashutosh P. Jadhav, Jin Soo Lee, Götz Thomalla, Simon Nagel, Qingwu Yang, Osama O. Zaidat, Zhongming Qiu, Zhongrong Miao, Soma Banerjee, Thanh N. Nguyen

Bibliographic record

VenueStroke Vascular and Interventional Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersH. Lundbeck A/SSchweizerische Akademie der Medizinischen WissenschaftenAllerganSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungBristol-Myers SquibbEli Lilly and CompanyAstraZenecaCSL BehringAlexion PharmaceuticalsNovo NordiskTeva Pharmaceutical IndustriesDaiichi-SankyoStrykerPfizerNational Science Foundation
KeywordsEtiologyMedicineThrombolysisOcclusionStroke (engine)Posterior communicating arteryStentSurgeryCardiologyInternal medicineInternal carotid arteryMyocardial infarctionPhysics

Abstract

fetched live from OpenAlex

Background: Two recent trials demonstrated a benefit for endovascular therapy (EVT) in the treatment of basilar artery occlusion (BAO). In light of the expected increase in the use of EVT for BAO, we sought to understand the technique preferences of neurointerventionalists performing EVT for BAO. Methods: We conducted an international online survey of physician opinions on the use of EVT in BAO between January and March 2022. The survey was distributed through stroke and neurointerventional organizations. Survey questions examined selection of patients for the procedure and the techniques currently used for EVT in BAO. Responses from neurointerventionalists were analyzed. Results: More than 3000 participants were invited yielding 1245 respondents, of whom 543 were classified as neurointerventionalists across 52 countries and included in this analysis. Most neurointerventionalists would proceed to EVT for occlusions of the V4 segment, the basilar artery, or the posterior cerebral artery, without regard for prior intravenous thrombolysis. For BAO of embolic etiology, aspiration only thrombectomy was the preferred method of 50.3% of neurointerventionalists. For BAO of intracranial atherosclerotic disease etiology, combined stent retriever and aspiration thrombectomy was the preferred method of 40.5% of neurointerventionalists. The majority of neurointerventionalists (88.0%) would proceed to stenting after 3 or fewer failed passes for patients with BAO of intracranial atherosclerotic disease etiology. In patients undergoing stenting, aspirin and clopidogrel was the most common antiplatelet regime (52.4%). Conclusions: Among the surveyed neurointerventionalists, the most common techniques for EVT of patients with BAO were contact aspiration or combined stent retriever with aspiration thrombectomy. For patients with BAO due to intracranial atherosclerotic disease, the majority of neurointerventionalists were willing to stent and do so most often after 3 or fewer failed passes and with the use of dual antiplatelet medications. Further study is needed to determine the optimal technique for EVT of BAO with or without intracranial atherosclerotic disease.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.299
Teacher spread0.282 · 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 teacher head, not a consensus.

Study designObservational
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

Citations27
Published2022
Admission routes1
Has abstractyes

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