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Record W4386307419 · doi:10.3389/fcvm.2023.1220017

Global eligibility and cost effectiveness of icosapent ethyl in primary and secondary cardiovascular prevention

2023· review· en· W4386307419 on OpenAlexaboutno aff
Peter P. Tóth, Jean Ferrières, M Waters, Martin Bødtker Mortensen, N. Lan, Nathan D. Wong

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2023
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
FundersAmarin PharmaAmarin CorporationEli Lilly and Company
KeywordsMedicinePrimary preventionPrimary (astronomy)Internal medicineCardiologyIntensive care medicineDisease

Abstract

fetched live from OpenAlex

Icosapent ethyl (IPE) is a purified eicosapentaenoic acid-only omega-3 fatty acid that significantly reduced cardiovascular (CV) events in patients receiving statins with established cardiovascular disease (CVD) and those with diabetes and additional risk factors in the pivotal REDUCE-IT trial. Since the publication of REDUCE-IT, there has been global interest in determining IPE eligibility in different patient populations, the proportion of patients who may benefit from IPE, and cost effectiveness of IPE in primary and secondary prevention settings. The aim of this review is to summarize information from eligibility and cost effectiveness studies of IPE to date. A total of sixteen studies were reviewed, involving 2,068,111 patients in the primary or secondary prevention settings worldwide. Up to forty-five percent of patients were eligible for IPE, depending on the selection criteria used (ie, REDUCE-IT criteria, US Food and Drug Administration label, Health Canada label, practice guidelines) and the population studied. Overall, eight cost-effectiveness studies across the United States, Canada, Germany, Israel, and Australia were included in this review and findings indicated that IPE is particularly cost effective in patients with established CVD.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.045
GPT teacher head0.372
Teacher spread0.328 · 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 designOther design
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

Citations6
Published2023
Admission routes1
Has abstractyes

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