Evidence map›Paper›PMID 35955920›Full record

ArticleInternational journal of molecular sciences2022

Identification of Myocardial Insulin Resistance by Using Liver Tests: A Simple Approach for Clinical Practice.

José Raúl Herance, Queralt Martín-Saladich, Mayra Alejandra Velásquez, Cristina Hernandez, Carolina Aparicio, Clara Ramirez-Serra, Roser Ferrer, Marina Giralt-Arnaiz, Miguel Ángel González-Ballester, Juan M Pericàs and 3 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Observational
  3. Brain [Brain communications · 2025
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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

13 authors at 3 institutions in 1 country.

José Raúl HeranceMedical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.ORCID 0000-0001-7178-3290
Queralt Martín-SaladichMedical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.ORCID 0000-0003-4798-1558
Mayra Alejandra VelásquezDiabetes and Metabolism Research Group, Vall d'Hebron Research Institute (VHIR), Endocrinology Department, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Cristina HernandezDiabetes and Metabolism Research Group, Vall d'Hebron Research Institute (VHIR), Endocrinology Department, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.ORCID 0000-0002-3109-1721
Carolina AparicioMedical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Clara Ramirez-SerraClinical Biochemistry Research Group, Vall d'Hebron Research Institute (VHIR), Biochemical Core Facilities, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Roser FerrerClinical Biochemistry Research Group, Vall d'Hebron Research Institute (VHIR), Biochemical Core Facilities, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.ORCID 0000-0002-8925-3172
Marina Giralt-ArnaizClinical Biochemistry Research Group, Vall d'Hebron Research Institute (VHIR), Biochemical Core Facilities, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Miguel Ángel González-BallesterBCN Medtech Group, Information and Communication Technologies Department, Pompeu Fabra University, 08018 Barcelona, Spain.ORCID 0000-0002-9227-6826
Juan M PericàsLiver Diseases Research Group, Vall d'Hebron Research Institute (VHIR), Liver Unit, Vall d'Hebron University Hospital, 08035 Barcelona, Spain.ORCID 0000-0002-3645-3293
Joan Castell-ConesaMedical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Santiago Aguadé-BruixMedical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.
Rafael SimóDiabetes and Metabolism Research Group, Vall d'Hebron Research Institute (VHIR), Endocrinology Department, Vall d'Hebron University Hospital, Autonomous University Barcelona, 08035 Barcelona, Spain.ORCID 0000-0003-0475-3096
Vall d'Hebron Institut de Recerca · ESInstituto de Salud Carlos III · ESUniversitat Pompeu Fabra · ES

Funding

Government of Catalonia 2017SGR1303Instituto de Salud Carlos III PI16/02064, PI20/01588
6 · The paper itself

Abstract

backgroundWe report that myocardial insulin resistance (mIR) occurs in around 60% of patients with type 2 diabetes (T2D) and was associated with higher cardiovascular risk in comparison with patients with insulin-sensitive myocardium (mIS). These two phenotypes (mIR vs. mIS) can only be assessed using time-consuming and expensive methods. The aim of the present study is to search a simple and reliable surrogate to identify both phenotypes.

methodsForty-seven patients with T2D underwent myocardial [18F]FDG PET/CT at baseline and after a hyperinsulinemic-euglycemic clamp (HEC) to determine mIR were prospectively recruited. Biochemical assessments were performed before and after the HEC. Baseline hepatic steatosis index and index of hepatic fibrosis (FIB-4) were calculated. Furthermore, liver stiffness measurement was performed using transient elastography.

resultsThe best model to predict the presence of mIR was the combination of transaminases, protein levels, FIB-4 score and HOMA (AUC = 0.95; sensibility: 0.81; specificity: 0.95). We observed significantly higher levels of fibrosis in patients with mIR than in those with mIS (

conclusionsThe combination of HOMA, protein, transaminases and FIB-4 is a simple and reliable tool for identifying mIR in patients with T2D. This information will be useful to improve the stratification of cardiovascular risk in T2D.

Indexed as

Diabetes Mellitus, Type 2Insulin ResistanceNon-alcoholic Fatty Liver DiseaseFibrosisHumansLiverMyocardiumPositron Emission Tomography Computed TomographyTransaminasesTransaminasescardiovascular riskmyocardial insulin resistancenon-alcoholic fatty liver diseasetype 2 diabetes

Identifiers

PMID35955920
PMCPMC9369008
OpenAlexW4290579674

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.