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Record W2344634324 · doi:10.1161/circresaha.116.307005

Evolving Treatments for Acute Ischemic Stroke

2016· review· en· W2344634324 on OpenAlexaff
Charlotte Zerna, Janka Hegedus, Michael D. Hill

Bibliographic record

VenueCirculation Research · 2016
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineThrombolysisNeurovascular bundleStroke (engine)Acute strokeTissue plasminogen activatorIntensive care medicineIschemic strokeInternal medicineCardiologyIschemiaSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

The purpose of this article is to review advances in stroke treatment in the hyperacute period. With recent evolutions of technology in the fields of imaging, thrombectomy devices, and emergency room workflow management, as well as improvement in statistical methods and study design, there have been ground breaking changes in the treatment of acute ischemic stroke. We describe how stroke presents as a clinical syndrome and how imaging as the most important biomarker will help differentiate between stroke subtypes and treatment eligibility. The evolution of hyperacute treatment has led to the current standard of care: intravenous thrombolysis with tissue-type plasminogen activator and endovascular treatment for proximal vessel occlusion in the anterior cerebral circulation. All patients with acute ischemic stroke are in need of hyperacute secondary prevention because the risk of recurrence is highest closest to the index event. The dominant themes of modern stroke care are the use of neurovascular imaging and speed of diagnosis and treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.171
GPT teacher head0.484
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations51
Published2016
Admission routes1
Has abstractyes

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