Evidence map›Paper›PMID 41126192›Full record

ArticleCardiovascular diabetology2025

AI-quantified epicardial adipose tissue and prediction of future myocardial infarction in patients with cardiometabolic disease: a post-hoc analysis from the SCOT-HEART trial.

Jolien Geers, Nipun Manral, Caroline Park, Guadalupe Flores Tomasino, Kajetan Grodecki, Joel Lenell, Mikolaj Buchwald, Aryabod Razipour, Jacek Kwiecinski, Hidenari Matsumoto and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

18 authors.

Jolien GeersBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Nipun ManralBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Caroline ParkBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Guadalupe Flores TomasinoBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Kajetan GrodeckiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Joel LenellBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Mikolaj BuchwaldDepartment of Medicine, Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Aryabod RazipourBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Jacek KwiecinskiDepartment of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland.
Hidenari MatsumotoDepartment of Cardiology, Kusatsu Heart Center, Kusatsu, Shiga, Japan.
Mohamed MarwanDepartment of Cardiology, Friedrich-Alexander-University Erlangen-Nurnberg, Erlangen, Germany.
Stephan AchenbachDepartment of Cardiology, Friedrich-Alexander-University Erlangen-Nurnberg, Erlangen, Germany.
Daniel S BermanDepartment of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Marc R DweckBHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
David E NewbyBHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Piotr J SlomkaDepartment of Medicine, Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Michelle C Williams *BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Damini Dey *Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA. Damini.Dey@cshs.org.

Funding

NHLBI NIH HHS 1R01HL148787-01A1
6 · The paper itself

Abstract

backgroundEpicardial adipose tissue is gaining increasing interest as a cardiometabolic imaging biomarker, but its exact role in coronary artery disease is not fully understood. This study aimed to investigate the relationship between epicardial adipose tissue, coronary plaque characteristics, and risk of myocardial infarction in patients with suspected coronary artery disease, and in those with concomitant cardiometabolic disease.

methodsIn a post-hoc analysis of the SCOT-HEART trial, epicardial adipose tissue volume and attenuation were quantified automatically from computed tomography (CT) angiography using deep-learning. Quantitative and high-risk coronary plaque characteristics were also assessed. The primary endpoint was fatal or non-fatal myocardial infarction.

resultsThe study population consisted of 1770 patients (58 ± 9 years, 56% males) of whom 313 (18%) with cardiometabolic disease. Epicardial adipose tissue volume was higher in patients withcardiometabolic disease (123 ± 44 versus 88 ± 36 mL, p < 0.001), and increased with the coronary calcium score (0: 82 ± 35 mL, 1-400: 97 ± 38 mL, > 400: 113 ± 44 mL; p < 0.001), and low-attenuation plaque burden (burden ≤ 4%: 85 ± 36mL, burden > 4%: 103 ± 41mL; p < 0.001), while there were no interactions between these features and epicardial adipose tissue attenuation (p > 0.05 for all). During a median follow-up of 8.6 years, 82 (4.6%) patients experienced myocardial infarction. In the total study cohort, epicardial adipose tissue volume predicted myocardial infarction both in univariable analysis, and after adjustment for established markers of cardiovascular risk. In patients with cardiometabolic disease, epicardial adipose tissue volume independently predicted myocardial infarction after adjustment for clinical risk factors and plaque features but this relationship was not found in those without cardiometabolic disease.

conclusionsCT-derived Epicardial adipose tissue volume correlates with quantitative and high-risk plaque features, and independently predicts risk of myocardial infarction in patients with cardiometabolic disease.

Indexed as

Adipose TissueAdiposityComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseDeep LearningMetabolic SyndromeMyocardial InfarctionPericardiumAgedCardiometabolic Risk FactorsEpicardial Adipose TissueFemaleHumansMaleMiddle AgedComputed tomography angiographyEpicardial adipose tissueMyocardial infarctionRisk prediction

Identifiers

PMID41126192
PMCPMC12542024

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.