Evidence map›Paper›PMID 27678433›Full record

Trial reportJournal of clinical lipidology

Assessment of postprandial triglycerides in clinical practice: Validation in a general population and coronary heart disease patients.

Pablo Perez-Martinez, Juan F Alcala-Diaz, Edmon K Kabagambe, Antonio Garcia-Rios, Michael Y Tsai, Javier Delgado-Lista, Genovefa Kolovou, Robert J Straka, Francisco Gomez-Delgado, Paul N Hopkins and 14 more

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of clinical lipidology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

9 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Palmar Striated Xanthomas in Clinical Practice.Journal of the Endocrine Society · 2022
    Article
  4. Article
  5. Observational
  6. Who would benefit most from postprandial lipid screening?Clinical nutrition (Edinburgh, Scotland) · 2021
    Article
  7. Article
  8. Article
  9. Review
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

24 authors at 12 institutions in 4 countries.

Pablo Perez-MartinezLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: pablopermar@yahoo.es.
Juan F Alcala-DiazLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Edmon K KabagambeDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Antonio Garcia-RiosLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Michael Y TsaiDepartment of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, USA.
Javier Delgado-ListaLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Genovefa Kolovou1st Cardiology Department, Onassis Cardiac Surgery Center, Athens, Greece.
Robert J StrakaDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA.
Francisco Gomez-DelgadoLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Paul N HopkinsDepartment of Internal Medicine, University of Utah Health Sciences Center, Salt Lake City, UT, USA.
Carmen MarinLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Ingrid BoreckiDivision of Statistical Genomics in the Center for Genome Sciences of the Washington University, St. Louis, USA.
Elena M Yubero-SerranoLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
James E HixsonHuman Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA.
Antonio CamargoLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Michael A ProvinceDepartment of Genetics Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA.
Javier Lopez-MorenoLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Fernando Rodriguez-CantalejoBiochemical Laboratory, Hospital Universitario Reina Sofia, Cordoba, Spain.
Francisco J TinahonesCIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Servicio de Endocrinologia y Nutricion, Hospital Clinico Virgen de la Victoria, Malaga, Spain.
Dimitri P MikhailidisDepartment of Clinical Biochemistry, Royal Free Hospital Campus, University College London Medical School, University College London, London, UK.
Francisco Perez-JimenezLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Donna K ArnettDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Jose M OrdovasJean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University School of Medicine, Boston, MA, USA; Department of Epidemiology, National Center of Cardiovascular Investigations, Madrid, Spain; Madrid Institute of Advanced Studies-Food, Madrid, Spain.
Jose Lopez-MirandaLipid and Atherosclerosis Unit, Department of Internal Medicine, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain; CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
Instituto Maimónides de Investigación Biomédica de Córdoba · ESInstituto de Salud Carlos III · ESUniversity of Córdoba · ESUniversity of Minnesota · USHospital Universitario Reina Sofía · ESJean Mayer Human Nutrition Research Center on Aging · USOnassis Cardiac Surgery Center · GRThe Royal Free Hospital · GBThe University of Texas Health Science Center at Houston · USUniversity of Alabama at Birmingham · USUniversity of Utah · USVanderbilt University Medical Center · US

Funding

Genetic and Environmental Determinants of TriglyceridesU01HL072524 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ARNETT, DONNA K · 2002 to 2008
$11.9M
NHLBI NIH HHS U01 HL072524
6 · The paper itself

Abstract

backgroundPrevious studies have suggested that for clinical purposes, subjects with fasting triglycerides (TGs) between 89-180 mg/dl (1-2 mmol/l) would benefit from postprandial TGs testing.

objectiveTo determine the postprandial TG response in 2 independent studies and validate who should benefit diagnostically from an oral-fat tolerance test (OFTT) in clinical practice.

methodsA population of 1002 patients with coronary heart disease (CHD) from the CORDIOPREV clinical trial and 1115 white US subjects from the GOLDN study underwent OFTTs. Subjects were classified into 3 groups according to fasting cut points of TGs to predict the usefulness of OFTT: (1) TG < 89 mg/dl (<1 mmol/l); (2) TG, 89-180 mg/dl (1-2 mmol/l); and (3) TG > 180 mg/dl (>2 mmol/l). Postprandial TG concentration at any point > 220 mg/dl (>2.5 mmol/l) has been pre-established as an undesirable postprandial response.

resultsOf the total, 49% patients with CHD and 42% from the general population showed an undesirable response after the OFTT. The prevalence of undesirable postprandial TG in the CORDIOPREV clinical trial was 12.8, 50.3, and 89.7%, in group 1, 2, and 3, respectively (P < .001) and 11.2, 58.1, and 97.5% in group 1, 2, and 3, respectively (P < .001) in the GOLDN study.

conclusionsThese two studies validate the predictive values reported in a previous consensus. Moreover, the findings of the CORDIOPREV and GOLDN studies show that an OFTT is useful to identify postprandial hyperlipidemia in subjects with fasting TG between 1-2 mmol/l (89-180 mg/dL), because approximately half of them have hidden postprandial hyperlipidemia, which may influence treatment. An OFTT does not provide additional information regarding postprandial hyperlipidemia in subjects with low TG (<1 mmol/l, <89 mg/dL) or increased TG (>2 mmol/l, >180 mg/dl).

Indexed as

AdultAgedAge FactorsCoronary Artery DiseaseDietary FatsFemaleHumansHyperlipidemiasLogistic ModelsMaleMiddle AgedOdds RatioPostprandial PeriodPrevalenceTriglyceridesDietary FatsTriglyceridesCORDIOPREV studyCoronary heart diseaseGOLDN studyOral-fat tolerance testPostprandial lipemiaTriglycerides

Identifiers

PMID27678433
PMCPMC7025632
OpenAlexW2409744366

What OpenQuestion holds

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Registered trials

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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.