Alberto García-Lledó1, José L Moya-Mur2, Virginia Ponz-Mir3, Susana Novo-Aparicio4, Azucena Sanz-Barrio3, Concepción Álvarez-Sanz4, Ana de Santiago-Nocito5. 1. Department of Cardiology, University Hospital Principe de Asturias, and Department of Medicine, University of Alcalá, Alcalá de Henares, Spain. alberto.garcia-lledo@uah.es. 2. Department of Cardiology University Hospital Ramón y Cajal, Madrid, Spain. 3. Department of Cardiology, University Hospital Principe de Asturias, and Department of Medicine, University of Alcalá, Alcalá de Henares, Spain. 4. Department of Radiology University Hospital Príncipe de Asturias, Alcalá de Henares, Spain. 5. GAI-Guadalajara, SESCAM, Guadalajara, Spain.
Abstract
BACKGROUND: Risk score systems (RSS) were designed to estimate the risk of cardiac events. Their ability to predict coronary atherosclerosis (CA) has not been established. HYPOTHESIS: Risk score systems can predict presence of CA in patients without typical symptoms or ischemia. Because design of each RSS is different, their predictive value could also differ. METHODS: A retrospective analysis was done on patients from a low-risk region referred for cardiac multislice computed tomography (MSCT). The sample included low- to intermediate-risk patients with nontypical chest pain and asymptomatic high-risk patients. Patients with documented ischemia were excluded. Three RSS were determined: Framingham Risk Score (FRS), Regicor (FRS calibrated for Spanish population), and Systematic Coronary Risk Evaluation (SCORE). Coronary arteries were investigated to determine calcium score and presence of protruding atheromas. RESULTS: We analyzed 582 patients (53.8% male; mean age 51 ± 11.5 years). Their mean estimated risk was intermediate: 15.6 ± 10.4 by FRS, 6.3 ± 4.3 by Regicor, and 3.9 ± 4.1 by SCORE. The MSCT showed no CA in 38.8%, nonobstructive plaques in 28.7%, and obstructive ones in 32.5%. The ability of the RSS to predict CA was not significantly different, with moderate diagnostic value (areas under ROC curves, 0.72-0.65). The prevalence of CA was high in low-risk patients: 40%, 47%, and 53% in FRS, Regicor, and SCORE low-risk patients, respectively. CONCLUSIONS: Risk score systems have only moderate diagnostic value to predict presence of CA, without significant differences among them. Coronary artery disease is highly prevalent in patients considered low risk.
BACKGROUND: Risk score systems (RSS) were designed to estimate the risk of cardiac events. Their ability to predict coronary atherosclerosis (CA) has not been established. HYPOTHESIS: Risk score systems can predict presence of CA in patients without typical symptoms or ischemia. Because design of each RSS is different, their predictive value could also differ. METHODS: A retrospective analysis was done on patients from a low-risk region referred for cardiac multislice computed tomography (MSCT). The sample included low- to intermediate-risk patients with nontypical chest pain and asymptomatic high-risk patients. Patients with documented ischemia were excluded. Three RSS were determined: Framingham Risk Score (FRS), Regicor (FRS calibrated for Spanish population), and Systematic Coronary Risk Evaluation (SCORE). Coronary arteries were investigated to determine calcium score and presence of protruding atheromas. RESULTS: We analyzed 582 patients (53.8% male; mean age 51 ± 11.5 years). Their mean estimated risk was intermediate: 15.6 ± 10.4 by FRS, 6.3 ± 4.3 by Regicor, and 3.9 ± 4.1 by SCORE. The MSCT showed no CA in 38.8%, nonobstructive plaques in 28.7%, and obstructive ones in 32.5%. The ability of the RSS to predict CA was not significantly different, with moderate diagnostic value (areas under ROC curves, 0.72-0.65). The prevalence of CA was high in low-risk patients: 40%, 47%, and 53% in FRS, Regicor, and SCORE low-risk patients, respectively. CONCLUSIONS: Risk score systems have only moderate diagnostic value to predict presence of CA, without significant differences among them. Coronary artery disease is highly prevalent in patients considered low risk.
Authors: Jaume Marrugat; Pascual Solanas; Ralph D'Agostino; Lisa Sullivan; José Ordovas; Ferran Cordón; Rafael Ramos; Joan Sala; Rafael Masià; Izabella Rohlfs; Roberto Elosua; William B Kannel Journal: Rev Esp Cardiol Date: 2003-03 Impact factor: 4.753
Authors: Alexander W Leber; Andreas Knez; Franz von Ziegler; Alexander Becker; Konstantin Nikolaou; Stephan Paul; Bernd Wintersperger; Maximilian Reiser; Christoph R Becker; Gerhard Steinbeck; Peter Boekstegers Journal: J Am Coll Cardiol Date: 2005-07-05 Impact factor: 24.094
Authors: Alberto García-Lledó; José L Moya-Mur; Virginia Ponz-Mir; Susana Novo-Aparicio; Azucena Sanz-Barrio; Concepción Álvarez-Sanz; Ana de Santiago-Nocito Journal: Clin Cardiol Date: 2016-09-06 Impact factor: 2.882
Authors: Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel Journal: Circulation Date: 2008-01-22 Impact factor: 29.690
Authors: Frank Breuckmann; Jan Olligs; Liane Hinrichs; Matthias Koopmann; Michael Lichtenberg; Dirk Böse; Dieter Fischer; Lars Eckardt; Johannes Waltenberger; J Lee Garvey Journal: Clin Cardiol Date: 2016-03 Impact factor: 2.882
Authors: Alberto García-Lledó; José L Moya-Mur; Virginia Ponz-Mir; Susana Novo-Aparicio; Azucena Sanz-Barrio; Concepción Álvarez-Sanz; Ana de Santiago-Nocito Journal: Clin Cardiol Date: 2016-09-06 Impact factor: 2.882
Authors: Revathi Balakrishnan; Brian Nguyen; Roy Raad; Robert Donnino; David P Naidich; Jill E Jacobs; Harmony R Reynolds Journal: Clin Cardiol Date: 2017-03-16 Impact factor: 2.882
Authors: Daan Ties; Paulien van Dorp; Gabija Pundziute; Erik Lipsic; Carlijn M van der Aalst; Matthijs Oudkerk; Harry J de Koning; Rozemarijn Vliegenthart; Pim van der Harst Journal: J Clin Med Date: 2022-05-24 Impact factor: 4.964