Computed tomography and coronary artery calcium score for screening of coronary artery disease and cardiovascular risk management in asymptomatic individuals

Sara Joan Pinto-Sietsma, Birgitta K. Velthuis, Nick S. Nurmohamed, Rozemarijn Vliegenthart, Fabrice M.A.C. Martens*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Several risk prediction models exist to predict atherosclerotic cardiovascular disease in asymptomatic individuals, but systematic reviews have generally found these models to be of limited utility. The coronary artery calcium score (CACS) offers an improvement in risk prediction, yet its role remains contentious. Notably, its negative predictive value has a high ability to rule out clinically relevant atherosclerotic cardiovascular disease. Nonetheless, CACS 0 does not permanently reclassify to a lower cardiovascular risk and periodic reassessment every 5 to 10 years remains necessary. Conversely, elevated CACS (> 100 or > 75th percentile adjusted for age, sex and ethnicity) can reclassify intermediate-risk individuals to a high risk, benefiting from preventive medication. The forthcoming update to the Dutch cardiovascular risk management guideline intends to re-position CACS for cardiovascular risk assessment as such in asymptomatic individuals. Beyond CACS as a single number, several guidelines recommend coronary CT angiography (CCTA), which provides additional information about luminal stenosis and (high-risk) plaque composition, as the first choice of test in symptomatic patients and high-risk patients. Ongoing randomised studies will have to determine the value of atherosclerosis evaluation with CCTA for primary prevention in asymptomatic individuals.

Original languageEnglish
Pages (from-to)371–377
Number of pages7
JournalNetherlands Heart Journal
Volume32
Issue number11
DOIs
Publication statusPublished - 2024

Keywords

  • (Non)-contrast coronary CT scan
  • Atherosclerosis cardiovascular disease
  • Coronary calcium scoring
  • Risk prediction

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