Evidence map›Paper›PMID 41185007›Full record

ReviewCardiovascular diabetology2025

Hunting for a coronary artery disease diagnosis in asymptomatic patients with diabetes mellitus: if, how and when.

Francesca Santilli, Michael J Blaha, Fabrizio Ricci, Paola Simeone

Abstract readReview
In one paragraph

Review in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

4 authors.

Francesca SantilliDepartment of Medicine and Aging, and Center for Advanced Studies and Technology (CAST), G. d'Annunzio University of Chieti-Pescara, Luigi Polacchi, 66013, Chieti, Italy. francesca.santilli@unich.it.
Michael J BlahaJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Blalock 524D1, 600 N. Wolfe Street, Baltimore, MD, 21287, USA.
Fabrizio RicciDepartment of Neuroscience, Imaging and Clinical Sciences, G.d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Paola SimeoneDepartment of Medicine and Aging, and Center for Advanced Studies and Technology (CAST), G. d'Annunzio University of Chieti-Pescara, Luigi Polacchi, 66013, Chieti, Italy.

Funding

European Union-Next Generation EU Under the Italian Ministry of University and Research (MUR) National Innovation Ecosystem Grant ECS00000041-VITALITY-D73C22000840006PRIN 2022 PRJ-0273
6 · The paper itself

Abstract

Cardiovascular disease is a leading cause of morbidity and mortality in individuals with type 2 diabetes. This population faces an increased risk of coronary artery disease due to accelerated atherosclerosis, endothelial dysfunction and chronic inflammation. A substantial proportion of cases remain clinically silent, with coronary artery disease often undetected until the occurrence of acute events. This silent progression poses a significant challenge for timely diagnosis and prevention. This review explores the prevalence, mechanisms, and prognosis of asymptomatic coronary artery disease in type 2 diabetes, focusing on current strategies for cardiovascular risk assessment and screening. While traditional risk factors such as hypertension, dyslipidemia, and hyperglycemia remain central to clinical evaluation, they often fail to fully capture the residual cardiovascular risk in diabetic patients. Advances in imaging, particularly coronary calcium scoring and computed tomography angiography, allow for the direct visualization of total plaque burden, providing a more refined assessment of risk. Functional tests and novel biomarkers, including high-sensitivity C-reactive protein and lipoprotein(a), further enhance the precision of risk stratification. Despite these advances, the clinical value of routine screening in asymptomatic diabetic individuals remains controversial. Evidence suggests that a selective, risk-based approach to screening may be more effective than universal testing, identifying high-risk patients who could benefit from more intensive preventive therapies. Emerging technologies, such as artificial intelligence and machine learning, promise to improve risk prediction by integrating clinical, imaging, and biomarker data into personalized care pathways. The review emphasizes the need to move from a reactive approach, based on symptom-driven evaluation, to a proactive strategy aimed at early identification of subclinical disease. By combining advanced imaging techniques, biomarker profiling, and updated risk algorithms, clinicians can better tailor preventive interventions, reduce adverse cardiovascular outcomes, and optimize long-term care. Further prospective studies are required to define the most effective and cost-efficient screening protocols for asymptomatic coronary artery disease in individuals with diabetes.

Indexed as

Coronary AngiographyCoronary Artery DiseaseDiabetes Mellitus, Type 2Asymptomatic DiseasesBiomarkersComputed Tomography AngiographyEarly DiagnosisHeart Disease Risk FactorsHumansPredictive Value of TestsPrevalencePrognosisRisk AssessmentRisk FactorsBiomarkers

Identifiers

PMID41185007
PMCPMC12581275

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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.