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Record W3157139271 · doi:10.1161/strokeaha.120.033994

Optimal Medical Management of Asymptomatic Carotid Stenosis

2021· review· en· W3157139271 on OpenAlexaff
Daniel G. Hackam

Bibliographic record

VenueStroke · 2021
Typereview
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAsymptomaticRevascularizationGlycemicCardiologyMedical therapyStenosisInternal medicineStroke (engine)Intensive care medicineMyocardial infarctionInsulin

Abstract

fetched live from OpenAlex

Asymptomatic carotid stenosis (ACS) due to atherosclerosis is a risk factor for ipsilateral ischemic cerebrovascular events and cognitive impairment. The prognosis of ACS has improved over the past 4 decades due largely to improvements in medical management. Most patients with ACS can be managed without revascularization, but some patients with vulnerable plaque should be considered for revascularization. Regardless of the decision to refer for revascularization, all patients with ACS should receive intensive medical management. This includes lifestyle modification (Mediterranean diet, exercise, and smoking cessation) and pharmacological therapy (antiplatelets, lipid-lowering agents, blood pressure reduction, and glycemic control). Patients with ACS often have atherosclerosis in other critical locations, and thus optimal medical therapy is likely to reduce events outside the carotid arteries. The nature of optimal medical therapy is described.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.887
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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)0.0020.000

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 head0.023
GPT teacher head0.314
Teacher spread0.291 · 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 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

Citations71
Published2021
Admission routes1
Has abstractyes

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