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Record W1993790467 · doi:10.2174/138161207780619019

Carotid Artery Atherosclerosis: What is the Evidence for Drug Action?

2007· review· en· W1993790467 on OpenAlexaff
Stella S. Daskalopoulou, Marios E. Daskalopoulos, Despina Perrea, Andrew Nicolaides, Christos D. Liapis

Bibliographic record

VenueCurrent Pharmaceutical Design · 2007
Typereview
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsRoyal Victoria HospitalMcGill University
Fundersnot available
KeywordsMedicineStenosisCardiologyStroke (engine)Internal medicineCarotid arteriesCoronary artery diseaseRadiology

Abstract

fetched live from OpenAlex

Carotid artery disease is a well-established cause of cerebrovascular events. This risk is predicted by the severity of stenosis and other plaque characteristics that can be documented using imaging techniques. Among these techniques, ultrasound is the most widely available. Increased carotid intima-media thickness (IMT) measured ultrasonically is associated with a higher risk for cerebrovascular as well as coronary heart disease. Furthermore, it is increasingly recognized that echolucent and heterogeneous carotid plaques in patients with high-grade carotid stenosis are associated with a greater risk for cerebrovascular events. Several local and systemic factors can influence plaque stability. Identifying the high-risk carotid plaque could improve selection for vascular intervention (surgery/angioplasty) and increase cost-effectiveness. Aggressive medical treatment should always be provided for these high-risk patients. For example, lipid-lowering, anthihypertensive and antiplatelet drugs decrease the carotid IMT, stabilize carotid plaques or reduce the risk of cerebrovascular and systemic events. Continuously evolving technology will lead to more accurate identification of high-risk carotid plaques. A combination of comprehensive non- or minimally-invasive imaging techniques together with measuring clinical and systemic biochemical markers of risk may facilitate the identification of the vulnerable plaque in the vulnerable patient, and help select the best treatment options.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.518
GPT teacher head0.516
Teacher spread0.002 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

Explore more

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