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REPEATED ENDOVASCULAR THROMBECTOMY FOR EARLY RECURRENT INTRACRANIAL LARGE VESSEL OCCLUSION

2017· other· en· W6889733450 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)OcclusionRadiological weaponRetrospective cohort studyEndovascular treatmentIschemic stroke

Abstract

fetched live from OpenAlex

Background and Purpose:Early recurrent intracranial large vessel occlusion (LVO) is uncommon and associated with poor outcome. The aim of this study was to describe the clinical and radiological features of patients with early recurrent LVO managed with repeat endovascular treatment.Methods:A retrospective analysis of ischemic stroke patients with LVO and more than one endovascular procedure within 10 days of the index stroke, treated at 9 stroke centers in New Zealand, Australia, Taiwan, Finland and Canada. Results:There were 35 patients [16 (46%) female; median age 67 (interquartile range, IQR: 50-76) years; 25 (71%) recurrent anterior circulation, 8 (23%) recurrent posterior circulation, 2 (6%) both anterior and posterior circulation LVO] included. Twenty (57%) had cardioembolic stroke etiology. The median time between procedures was 45 (IQR 16-120) hours and one patient had three procedures. Twenty-two patients (63%) had reocclusion in the same target vessel, 9 (41%) of whom had residual vessel wall irregularity after the initial procedure. Good outcomes (mRS 0-2) were achieved in 10 (29%) patients and favourable outcomes (mRS 0-3) in 17(49%). Patients with favourable outcome had lower baseline NIHSS (12 vs 18,p=0.05) and less recurrent posterior circulation LVOs (6% vs 39%,p=0.04). Two patients (6%) had symptomatic intracerebral hemorrhage. Eleven patients (31%) had died by 3 months. Conclusion:Early recurrent LVO can be safely managed with repeat endovascular treatment with favorable clinical outcome.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0270.015
Science and technology studies0.0020.002
Scholarly communication0.0130.023
Open science0.0190.020
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0230.014

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 head0.073
GPT teacher head0.366
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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