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Record W2333811085 · doi:10.2310/6670.2010.00023

Asymptomatic Carotid Stenosis: Mainly a Medical Condition

2010· article· en· W2333811085 on OpenAlexfundno aff
J. David Spence

Bibliographic record

VenueVascular · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsMedicineCarotid endarterectomyAsymptomaticStenosisTranscranial DopplerStroke (engine)Carotid stentingEndarterectomyRadiologyStentMagnetic resonance imagingSurgeryCardiologyInternal medicine

Abstract

fetched live from OpenAlex

At present approximately 70% of carotid endarterectomy and stenting in the United States is being performed for asymptomatic carotid stenosis (ACS). This is based on historical risks of ACS that no longer pertain in the era of intensive medical therapy with statins and other therapies. In the past, the surgical risk of 3% in clinical trials was marginally better than medical therapy for male patients with ACS; however, this is no longer the case. Even in the past, women with ACS did not benefit from endarterectomy. Except for patients with microemboli on transcranial Doppler (who have a 2-year risk of stroke of approximately 14%), the 2-year risk of stroke in ACS is now 1% or less. Endarterectomy or stenting should be reserved for the < 5% of patients with microemboli on transcranial Doppler ultrasonography. In future, 3 dimensional ultrasound detection of ulceration, and magnetic resonance imaging of vulnerable plaque may provide additional approaches to identifying those patients with ACS who may benefit from endarterectomy or stenting. Routine endarterectomy or stenting for patients with ACS should now be regarded as inappropriate.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations30
Published2010
Admission routes1
Has abstractyes

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