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Record W3094072653 · doi:10.1007/s11892-020-01343-7

The Road to Approval: a Perspective on the Role of Icosapent Ethyl in Cardiovascular Risk Reduction

2020· review· en· W3094072653 on OpenAlexaff
Xiaowen Wang, Subodh Verma, R. Preston Mason, Deepak L. Bhatt

Bibliographic record

VenueCurrent Diabetes Reports · 2020
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Toronto
FundersAmarin PharmaAmarin Corporation
KeywordsEicosapentaenoic acidMedicineClinical trialEthyl esterPharmacologyIntensive care medicineInternal medicineFatty acidPolyunsaturated fatty acidBiochemistryBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Epidemiological studies have long suggested the cardiovascular benefits of omega-3 fatty acids (OM3FAs). However, until recently, clinical trials using OM3FAs have been largely negative with respect to their cardioprotective effects. In this review, we aim to summarize key clinical trials, examine the clinical benefits of eicosapentaenoic acid (EPA) and potential mechanisms, and review the changes in guidelines and recommendations. RECENT FINDINGS: The Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial (REDUCE-IT) has demonstrated significant cardiovascular mortality benefits of purified EPA ethyl ester, with a 25% relative risk reduction in major cardiovascular events. As first of its class to be approved, icosapent ethyl offers a new option to further reduce cardiovascular risks in patients already treated with maximally tolerated statins.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.043
GPT teacher head0.360
Teacher spread0.317 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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