Evidence map›Paper›PMID 30644366›Full record

ArticleDiagnostic and interventional radiology (Ankara, Turkey)2019

Quantification of epicardial fat with cardiac CT angiography and association with cardiovascular risk factors in symptomatic patients: from the ALTER-BIO (Alternative Cardiovascular Bio-Imaging markers) registry.

Gianluca Milanese, Mario Silva, Livia Bruno, Matteo Goldoni, Giorgio Benedetti, Enrica Rossi, Caterina Ferrari, Ludovico La Grutta, Erica Maffei, Patrizia Toia and 4 more

Abstract readComparative Study
In one paragraph

Article in Diagnostic and interventional radiology (Ankara, Turkey), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  17. Recent technologies in cardiac imaging.Frontiers in medical technology · 2022
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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

14 authors.

Gianluca MilaneseDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Mario SilvaDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Livia BrunoDepartment of Radiology, University of Palermo, Palermo, Italy.
Matteo GoldoniDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Giorgio BenedettiDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Enrica RossiDivision of Radiology, University of Parma, Parma, Italy; Department of Radiology, Area Vasta 1/ASUR Marche, Urbino, Italy.
Caterina FerrariDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Ludovico La GruttaDepartment of Radiology, University of Palermo, Palermo, Italy.
Erica MaffeiDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Patrizia ToiaDepartment of Radiology, University of Palermo, Palermo, Italy.
Ernesto ForteCardiovascular Imaging Center, SDN IRCCS, Naples, Italy.
Riccardo C BonadonnaDivision of Endocrinology and Metabolic Diseases, Department of Medicine and Surgery, University of Parma, Parma, Italy.
Nicola SverzellatiDivision of Radiology, University of Parma, Parma, Italy; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Filippo CademartiriCardiovascular Imaging Center SDN IRCCS, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe aimed to assess the association between features of epicardial adipose tissue and demographic, morphometric and clinical data, in a large population of symptomatic patients with clinical indication to cardiac computed tomography (CT) angiography.

methodsEpicardial fat volume (EFV) and adipose CT density of 1379 patients undergoing cardiac CT angiography (918 men, 66.6%; age range, 18-93 years; median age, 64 years) were semi-automatically quantified. Clinical variables were compared between diabetic and nondiabetic patients to assess potential differences in EFV and adipose CT density. Multiple regression models were calculated to find the clinical variables with a significant association with EFV and adipose CT density.

resultsThe median EFV in diabetic patients (112.87 mL) was higher compared with nondiabetic patients (82.62 mL; P < 0.001). The explanatory model of the multivariable analysis showed the strongest associations between EFV and BMI (β=0.442) and age (β=0.365). Significant yet minor association was found with sex (β=0.203), arterial hypertension (β=0.072), active smoking (β=0.068), diabetes (β=0.068), hypercholesterolemia (β=0.046) and cardiac height (β=0.118). The mean density of epicardial adipose tissue was associated with BMI (β=0.384), age (β=0.105), smoking (β=0.088), and diabetes (β=0.085).

conclusionIn a large population of symptomatic patients, EFV is higher in diabetic patients compared with nondiabetic patients. Clinical variables are associated with quantitative features of epicardial fat.

Indexed as

Adipose TissueAdultAgedAged, 80 and overBiomarkersBody Mass IndexCardiovascular DiseasesComputed Tomography AngiographyDiabetes MellitusFemaleHumansHypercholesterolemiaHypertensionMaleMiddle AgedPericardiumBiomarkers

Identifiers

PMID30644366
PMCPMC6339622

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.