Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors

Abstract Background Coronary artery disease (CAD) is the third leading cause of death worldwide, so prevention and early diagnosis play important roles to reduce mortality and morbidity. Traditional risk-score assessments were used to find the at-risk patients in order to prevent or early treatment...

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Main Authors: Kiara Rezaie-Kalamtari, Zeinab Norouzi, Alireza Salmanipour, Hossein Mehrali
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:The Egyptian Heart Journal
Online Access:https://doi.org/10.1186/s43044-025-00608-4
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author Kiara Rezaie-Kalamtari
Zeinab Norouzi
Alireza Salmanipour
Hossein Mehrali
author_facet Kiara Rezaie-Kalamtari
Zeinab Norouzi
Alireza Salmanipour
Hossein Mehrali
author_sort Kiara Rezaie-Kalamtari
collection DOAJ
description Abstract Background Coronary artery disease (CAD) is the third leading cause of death worldwide, so prevention and early diagnosis play important roles to reduce mortality and morbidity. Traditional risk-score assessments were used to find the at-risk patients in order to prevent or early treatment of CAD. Adding imaging data to traditional risk-score systems will able us to find these patients more confidently and reduce the probable mismanagements. Main text Measuring the vascular calcification by coronary artery calcium (CAC) score can prepare valuable data for this purpose. Using CAC became more popular in recent years. The most applicable method to evaluate CAC is Agatston scoring using computed tomography (CT) scanning. Patients are classified into several subgroups: no evidence of CAD (score 0), mild CAD (score 1–10), minimal CAD (score 11–100), moderate CAD (score 101–400), and severe CAD (score > 400) and higher than1000 as the extreme risk of CVD events. Conclusions CAC assessment was recommended in the patients older than 40 years old with CAD risk factors, the ones with stable angina, borderline-to-intermediate-risk group, etc. According to the results of the CAC the patients may be candidate for further evaluation for needing revascularization, medical treatment, or routine follow-up. Adding artificial intelligence (AI) to CAC will prepare more data and can increase the reliability of our approach to the patients promising a bright future to improve this technology.
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institution Kabale University
issn 2090-911X
language English
publishDate 2025-01-01
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series The Egyptian Heart Journal
spelling doaj-art-230642d02ccf4c6591c89aa3b5477c3b2025-01-26T12:39:38ZengSpringerOpenThe Egyptian Heart Journal2090-911X2025-01-017711910.1186/s43044-025-00608-4Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factorsKiara Rezaie-Kalamtari0Zeinab Norouzi1Alireza Salmanipour2Hossein Mehrali3Rajaie Cardiovascular, Medical and Research InstituteRajaie Cardiovascular, Medical and Research InstituteRajaie Cardiovascular, Medical and Research InstituteRajaie Cardiovascular, Medical and Research InstituteAbstract Background Coronary artery disease (CAD) is the third leading cause of death worldwide, so prevention and early diagnosis play important roles to reduce mortality and morbidity. Traditional risk-score assessments were used to find the at-risk patients in order to prevent or early treatment of CAD. Adding imaging data to traditional risk-score systems will able us to find these patients more confidently and reduce the probable mismanagements. Main text Measuring the vascular calcification by coronary artery calcium (CAC) score can prepare valuable data for this purpose. Using CAC became more popular in recent years. The most applicable method to evaluate CAC is Agatston scoring using computed tomography (CT) scanning. Patients are classified into several subgroups: no evidence of CAD (score 0), mild CAD (score 1–10), minimal CAD (score 11–100), moderate CAD (score 101–400), and severe CAD (score > 400) and higher than1000 as the extreme risk of CVD events. Conclusions CAC assessment was recommended in the patients older than 40 years old with CAD risk factors, the ones with stable angina, borderline-to-intermediate-risk group, etc. According to the results of the CAC the patients may be candidate for further evaluation for needing revascularization, medical treatment, or routine follow-up. Adding artificial intelligence (AI) to CAC will prepare more data and can increase the reliability of our approach to the patients promising a bright future to improve this technology.https://doi.org/10.1186/s43044-025-00608-4
spellingShingle Kiara Rezaie-Kalamtari
Zeinab Norouzi
Alireza Salmanipour
Hossein Mehrali
Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
The Egyptian Heart Journal
title Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
title_full Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
title_fullStr Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
title_full_unstemmed Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
title_short Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors
title_sort updates on cad risk assessment using the coronary artery calcium score in combination with traditional risk factors
url https://doi.org/10.1186/s43044-025-00608-4
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AT alirezasalmanipour updatesoncadriskassessmentusingthecoronaryarterycalciumscoreincombinationwithtraditionalriskfactors
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