Evidence map›Paper›PMID 24951539›Full record

ReviewCardiovascular research2014

Novel concepts in HDL pharmacology.

Alan T Remaley, Giuseppe D Norata, Alberico L Catapano

Abstract readReview
In one paragraph

Review in Cardiovascular research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Molecular dynamics simulations of lipid nanodiscs.Biochimica et biophysica acta. Biomembranes · 2018
    Article
  7. Tertiary structure of apolipoprotein A-I in nascent high-density lipoproteins.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Fine mapping theNPJ aging and mechanisms of disease · 2015
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alan T RemaleyNational Heart, Lung and Blood Institute, NIH, 10 Center Drive, Bldg. 10, Rm. 2C-433, Bethesda, MD, USA aremaley1@cc.nih.gov.
Giuseppe D NorataDepartment of Pharmacological Sciences, Università degli Studi di Milano, Milano, Italy Center for the Study of Atherosclerosis, Società Italiana Studio Aterosclerosi, Ospedale Bassini, Cinisello Balsamo, Italy The Blizard Institute, Centre for Diabetes, Barts and The London School of Medicine & Dentistry, Queen Mary University, London, UK.
Alberico L CatapanoDepartment of Pharmacological Sciences, Università degli Studi di Milano, Milano, Italy IRCCS Multimedica, Milan, Italy.

Funding

Intramural NIH HHS
6 · The paper itself

Abstract

High-density lipoproteins (HDL) are a target for drug development because of their proposed anti-atherogenic properties. In this review, we will briefly discuss the currently established drugs for increasing HDL-C, namely niacin and fibrates, and some of their limitations. Next, we will focus on novel alternative therapies that are currently being developed for raising HDL-C, such as CETP inhibitors. Finally, we will conclude with a review of novel drugs that are being developed for modulating the function of HDL based on HDL mimetics. Gaps in our knowledge and the challenges that will have to be overcome for these new HDL based therapies will also be discussed.

Indexed as

AnimalsBiomarkersCardiovascular DiseasesCholesterol, HDLDrug DesignDyslipidemiasHumansHypolipidemic AgentsMolecular Targeted TherapyTreatment OutcomeUp-RegulationBiomarkersCholesterol, HDLHypolipidemic AgentsAtherosclerosisCardiovascular diseaseCholesterolDrugsHDL

Identifiers

PMID24951539
PMCPMC4133558

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.