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Record W4313394765 · doi:10.1161/svin.122.000595

Late Window Imaging Selection for Endovascular Therapy of Large Vessel Occlusion Stroke: An International Survey

2022· article· en· W4313394765 on OpenAlexafffund
Thanh N. Nguyen, Piers Klein, Anne Berberich, Simon Nagel, Mohamad Abdalkader, Ana Herning, Yimin Chen, Xiaochuan Huo, Zhongrong Miao, Sunil A. Sheth, Muhammad M. Qureshi, James E. Siegler, Simona Sacco, Daniel Strbian, Urs Fischer, Hiroshi Yamagami, Espen Saxhaug Kristoffersen, Volker Puetz, Wouter J. Schonewille, Georgios Tsivgoulis, Brian Drumm, Soma Banerjee, Jelle Demeestere, Fana Alemseged, Else Charlotte Sandset, Anita Arsovska, Kailash Krishnan, Permesh Singh Dhillon, Ángel Corredor, Rodrigo Rivera, Petra Šedová, Robert Mikulík, Hesham Masoud, Sheila Cristina Ouriques Martins, Thang Huy Nguyen, Xinfeng Liu, Yuyou Zhu, Fengli Li, Wan Asyraf Wan Zaidi, Marialuisa Zedde, Shadi Yaghi, Jian Miao, Violiza Inoa, Liqun Zhang, Rytis Masiliūnas, Peter Slade, Sarah Shali Matuja, João Pedro Marto, Patrik Michel, Jens Fiehler, Götz Thomalla, Alicia C. Castonguay, Maxim Mokin, Mark Parsons, Bruce Campbell, Dileep R. Yavagal, Diederik W.J. Dippel, Mayank Goyal, Osama O. Zaidat, Tudor G. Jovin, Wei Hu, Raul G. Nogueira, Zhongming Qiu, Jean Raymond, Gustavo Saposnik

Bibliographic record

VenueStroke Vascular and Interventional Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Toronto
FundersSchool of Life Sciences and Biotechnology Division of Life Sciences, Korea UniversityUniversitätsklinikum Hamburg-EppendorfMedical Center, University of PittsburghHealth Science Center, University of TennesseeUniversity of Health and Allied SciencesStiftelsen Norsk LuftambulanseLékařská fakulta, Masarykova univerzitaArmy Medical UniversityMasarykova UniverzitaImperial College LondonCentre Hospitalier Universitaire VaudoisNational and Kapodistrian University of AthensUniversité de LausanneUniversidade Federal do Rio Grande do SulSt. Antonius ZiekenhuisUniversity of Science and Technology of ChinaUniversiti Kebangsaan MalaysiaLeonard M. Miller School of MedicineUniversity of TorontoSyracuse UniversityUniversity of PittsburghHospital de Clínicas de Porto AlegreState University of New YorkTechnische Universität DresdenBrown UniversityUniversity of NottinghamImperial College Healthcare NHS TrustNottingham University Hospitals NHS TrustUniversity of MiamiUniversity of South Florida
KeywordsMagnetic resonance imagingMedicineStroke (engine)Perfusion scanningRadiologyMedical imagingOcclusionNeuroimagingPerfusionSurgery

Abstract

fetched live from OpenAlex

Background Current stroke guidelines recommend advanced imaging (computed tomography [CT] perfusion or magnetic resonance imaging) prior to endovascular therapy (EVT) in patients with late presentation of large vessel occlusion. Adherence to guidelines may be constrained by resources or timely access to imaging. We sought to understand the factors which influence late window imaging selection for EVT candidates with large vessel occlusion. Methods We conducted an international survey from January to May 2022. The questions aimed to identify advanced imaging and treatment decisions based on access to imaging, time delays, and simulated patient scenarios. Results There were 3000 invited participants and 1506 respondents, the majority (89.6%) from comprehensive stroke centers in high‐income countries. Neurointerventionalists comprised 31.8% and noninterventionalists 68.2% of respondents. Overall, 70.7% reported routine use of advanced imaging for late EVT selection, and 63.6% reported its usage in every case. There was greater availability of advanced imaging in comprehensive stroke centers versus primary stroke centers (67.0% versus 33.7%; P <0.0001), and high‐ versus low‐middle income countries (70.5% versus 44.5%; P <0.0001). When presented with a late window patient, 41.6% would complete CT perfusion or magnetic resonance imaging prior to EVT, 25.4% would perform CT perfusion or magnetic resonance imaging prior to IVT and EVT, and 25.8% would refer to EVT without advanced imaging. If advanced imaging was not readily available, 70.1% would refer a patient to EVT based on CT in the late window. Additional time delay within 20 minutes to obtain advanced imaging was considered acceptable in 77.7% of respondents. Conclusion Current guidelines for imaging late window EVT candidates are inconsistent with imaging decisions by physicians. Most respondents consider an imaging delay of greater than 20 minutes unacceptable. Access to advanced imaging was greater in comprehensive stroke centers and high‐income countries. In the case of limited access most respondents would consider EVT based on CT only.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.735

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 science0.0000.000
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 head0.016
GPT teacher head0.288
Teacher spread0.272 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations40
Published2022
Admission routes2
Has abstractyes

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