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Record W2103529894 · doi:10.2174/138955710791185046

Niacin: From Mechanisms of Action to Therapeutic Uses

2010· review· en· W2103529894 on OpenAlexaff
Maha A. Al‐Mohaissen, S Pun, Jiří Fröhlich

Bibliographic record

VenueMini-Reviews in Medicinal Chemistry · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsNiacinStatinResidual riskMedicineClinical trialPharmacologyLipoproteinCholesterolInternal medicineBioinformaticsBiology

Abstract

fetched live from OpenAlex

Niacin has broad spectrum lipid modifying and anti-atherosclerotic properties. It is the most effective medication available for raising raise high density lipoprotein (HDL) levels. Despite statin therapy there remains a considerable residual cardiovascular risk attributed to low HDL levels. Currently, statins decrease cardiovascular events and death by about 25-40%. Trials with surrogate endpoints have shown a decrease in endpoints by 60-90% when a combination of statin and niacin has been used. There is a growing interest in niacin in combination therapy to fill the treatment gap by modifying lipid parameters other than low density lipoprotein cholesterol. This review addresses the role of niacin in comprehensive lipid management with an emphasis on its mechanism of action, formulations, side effects, evidence from clinical trials and also focuses on practical issues related to niacin therapy.

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 score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.060
GPT teacher head0.366
Teacher spread0.306 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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