MétaCan
Menu
Back to cohort
Record W2022771791 · doi:10.2174/138945009789108783

Role of Statins in Peri-Operative Medicine

2009· review· en· W2022771791 on OpenAlexaff
Hema Bagry, F. Carli

Bibliographic record

VenueCurrent Drug Targets · 2009
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsSt. Boniface Hospital
Fundersnot available
KeywordsMedicineStatinPerioperativeCoronary artery diseaseHMG-CoA reductaseAtorvastatinCholesterolDiseaseInflammationStroke (engine)Internal medicineReductaseIntensive care medicineCardiologySurgeryEnzyme

Abstract

fetched live from OpenAlex

Statins are widely prescribed cholesterol lowering agents that exert their effects by inhibiting 3-hydroxy-3methylglutaryl co-enzyme A reductase. With their modulatory effects on the atherogenic lipid profile, the role of statin therapy is expanding amidst the growing obesity epidemic. The cholesterol lowering effects of statin therapy remains central in the long term management of coronary artery disease and cerebrovascular disease. While statin therapy is used commonly to target elevated LDL cholesterol, there is emerging evidence supporting its role during acute coronary syndromes and stroke. Clinical research into plaque histology, vulnerable high risk plaques and plaque rupture has improved our insight into the pathophysiology of these acute vascular events. Non lipid lowering effects of statin, the so called pleitrophic effects, have become the focal point of investigation. This review discusses recent experimental and clinical evidence supporting the role of statin in perioperative medicine.

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)0.001
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.039
GPT teacher head0.382
Teacher spread0.343 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Drug TargetsSame topicLipoproteins and Cardiovascular HealthFrench-language works237,207