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Record W2414799060 · doi:10.1080/14779072.2016.1196134

Imaging in acute stroke

2016· review· en· W2414799060 on OpenAlexaffabout
Prasanna Venkatesan Eswaradass, Ramana Appireddy, James Evans, Carol Huilian Tham, Sadanand Dey, Mohamed Najm, Bijoy K. Menon

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2016
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsHotchkiss Brain InstituteOntario Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)Acute strokeIschaemic strokePerfusion scanningNeuroimagingAngiographyIntensive care medicineRadiologyInternal medicinePerfusionIschemiaTissue plasminogen activator

Abstract

fetched live from OpenAlex

INTRODUCTION: Stroke is the third leading cause of death and disability in Canada. In the hyperacute stroke setting, the treating physician must make a time critical decision on the treatment of each patient. Recent advances in imaging help the treating physician identify the subgroup of patients eligible for acute treatment of ischaemic stroke. AREAS COVERED: In this review we will discuss Non-Contrast Computed Tomography (NCCT), CT-Angiography (CTA), and CT-Perfusion (CTP) in assessment of patients with acute ischaemic stroke and intracerebral haemorrhage. Intravenous tPA was the only proven therapy for acute ischaemic stroke presenting within 4.5 hours, until the five recent trials proved the efficacy of EVT for acute ischaemic stroke with proximal arterial occlusion. Imaging played a major role in patient selection in all five trials. Expert commentary: The challenge of rapid clinical assessment, review of imaging and timely treatment will continue to be made easier as the development and understanding of imaging progresses.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.008
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.346
Teacher spread0.322 · 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 designOther design
Domainnot available
GenreReview

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

Citations10
Published2016
Admission routes2
Has abstractyes

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