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Record W1867833955 · doi:10.1161/strokeaha.115.009215

Hemodynamic Features of Symptomatic Vertebrobasilar Disease

2015· article· en· W1867833955 on OpenAlexaff
Sepideh Amin‐Hanjani, Xinjian Du, Linda Rose‐Finnell, Dilip K. Pandey, DeJuran Richardson, Keith R. Thulborn, Mitchell S.V. Elkind, Gregory J. Zipfel, David S. Liebeskind, Frank L. Silver, Scott E. Kasner, Victor Aletich, Louis R. Caplan, Colin P. Derdeyn, Philip B. Gorelick, Fady T. Charbel, Hui Xie, M. Flannery, Hagai Ganin, Sean Ruland, Rebecca Grysiewicz, Aslam M. Khaja, Laura Pedelty, Fernando D. Testai, Archie Ong, Noam Epstein, Hurmina Muqtadar, Karriem S. Watson, Nada Mlinarevich, Maureen Hillmann, Joy Hirsch, Stephen Dashnaw, Philip M. Meyers, Josh Z. Willey, Edwina McNeill‐Simaan, Veronica Perez, Alberto Canaan, Wayna Paulino‐Hernandez, Katie D. Vo, Glenn L. Foster, Andria L. Ford, Abdullah Nassief, Abbie Bradley, Jannie Serna‐Northway, Lina Shiwani, Nancy Hantler, Jeffrey Alger, Sergio Godinez, Jeffrey L. Saver, Latisha K. Ali, Doojin Kim, Matthew Tenser, Michael T. Froehler, Radoslav Raychev, Sarah Song, Bruce Ovbiagele, Hermelinda Abcede, Peter G. Adamczyk, Neal Rao, Anil Yallapragada, Royya Modir, Jason D. Hinman, Aaron Tansy, Mateo Calderon‐Arnulphi, Sunil Sheth, Alireza Noorian, Kwan Ng, Conrad W Liang, Jignesh Gadhia, Hannah Smith, Gilda Avila, Johanna Avelar, David J. Mikulis, Jorn Fierstra, Eugen Hlasny, Leanne K. Casaubon, Mervyn D. I. Vergouwen, John Campo, Cheryl Jaigobin, Cherissa Astorga, Libby Kalman, Jeffrey Kramer, Susan Vaughan, Laura Owens, Brett Kissela, Tanya N. Turan, T P Jacobs, Scott Janis

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institutes of Health
KeywordsMedicineStenosisCardiologyStroke (engine)Internal medicineVertebrobasilar insufficiencyHemodynamicsVertebral arteryCollateral circulationOcclusionVascular diseaseRadiology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Atherosclerotic vertebrobasilar disease is an important cause of posterior circulation stroke. To examine the role of hemodynamic compromise, a prospective multicenter study, Vertebrobasilar Flow Evaluation and Risk of Transient Ischemic Attack and Stroke (VERiTAS), was conducted. Here, we report clinical features and vessel flow measurements from the study cohort. METHODS: Patients with recent vertebrobasilar transient ischemic attack or stroke and ≥50% atherosclerotic stenosis or occlusion in vertebral or basilar arteries (BA) were enrolled. Large-vessel flow in the vertebrobasilar territory was assessed using quantitative MRA. RESULTS: The cohort (n=72; 44% women) had a mean age of 65.6 years; 72% presented with ischemic stroke. Hypertension (93%) and hyperlipidemia (81%) were the most prevalent vascular risk factors. BA flows correlated negatively with percentage stenosis in the affected vessel and positively to the minimal diameter at the stenosis site (P<0.01). A relative threshold effect was evident, with flows dropping most significantly with ≥80% stenosis/occlusion (P<0.05). Tandem disease involving the BA and either/both vertebral arteries had the greatest negative impact on immediate downstream flow in the BA (43 mL/min versus 71 mL/min; P=0.01). Distal flow status assessment, based on an algorithm incorporating collateral flow by examining distal vessels (BA and posterior cerebral arteries), correlated neither with multifocality of disease nor with severity of the maximal stenosis. CONCLUSIONS: Flow in stenotic posterior circulation vessels correlates with residual diameter and drops significantly with tandem disease. However, distal flow status, incorporating collateral capacity, is not well predicted by the severity or location of the 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)0.000
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 score0.021
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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

Citations59
Published2015
Admission routes1
Has abstractyes

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