AIMS: Common carotid artery intima-media thickness (CCIMT) is widely used as a surrogate marker of atherosclerosis, given its predictive association with cardiovascular disease (CVD). The interpretation of CCIMT values has been hampered by the absence of reference values, however. We therefore aimed to establish reference intervals of CCIMT, obtained using the probably most accurate method at present (i.e. echotracking), to help interpretation of these measures. METHODS AND RESULTS: We combined CCIMT data obtained by echotracking on 24 871 individuals (53% men; age range 15-101 years) from 24 research centres worldwide. Individuals without CVD, cardiovascular risk factors (CV-RFs), and BP-, lipid-, and/or glucose-lowering medication constituted a healthy sub-population (n = 4234) used to establish sex-specific equations for percentiles of CCIMT across age. With these equations, we generated CCIMT Z-scores in different reference sub-populations, thereby allowing for a standardized comparison between observed and predicted ('normal') values from individuals of the same age and sex. In the sub-population without CVD and treatment (n = 14 609), and in men and women, respectively, CCIMT Z-scores were independently associated with systolic blood pressure [standardized βs 0.19 (95% CI: 0.16-0.22) and 0.18 (0.15-0.21)], smoking [0.25 (0.19-0.31) and 0.11 (0.04-0.18)], diabetes [0.19 (0.05-0.33) and 0.19 (0.02-0.36)], total-to-HDL cholesterol ratio [0.07 (0.04-0.10) and 0.05 (0.02-0.09)], and body mass index [0.14 (0.12-0.17) and 0.07 (0.04-0.10)]. CONCLUSION: We estimated age- and sex-specific percentiles of CCIMT in a healthy population and assessed the association of CV-RFs with CCIMT Z-scores, which enables comparison of IMT values for (patient) groups with different cardiovascular risk profiles, helping interpretation of such measures obtained both in research and clinical settings.
AIMS: Common carotid artery intima-media thickness (CCIMT) is widely used as a surrogate marker of atherosclerosis, given its predictive association with cardiovascular disease (CVD). The interpretation of CCIMT values has been hampered by the absence of reference values, however. We therefore aimed to establish reference intervals of CCIMT, obtained using the probably most accurate method at present (i.e. echotracking), to help interpretation of these measures. METHODS AND RESULTS: We combined CCIMT data obtained by echotracking on 24 871 individuals (53% men; age range 15-101 years) from 24 research centres worldwide. Individuals without CVD, cardiovascular risk factors (CV-RFs), and BP-, lipid-, and/or glucose-lowering medication constituted a healthy sub-population (n = 4234) used to establish sex-specific equations for percentiles of CCIMT across age. With these equations, we generated CCIMT Z-scores in different reference sub-populations, thereby allowing for a standardized comparison between observed and predicted ('normal') values from individuals of the same age and sex. In the sub-population without CVD and treatment (n = 14 609), and in men and women, respectively, CCIMT Z-scores were independently associated with systolic blood pressure [standardized βs 0.19 (95% CI: 0.16-0.22) and 0.18 (0.15-0.21)], smoking [0.25 (0.19-0.31) and 0.11 (0.04-0.18)], diabetes [0.19 (0.05-0.33) and 0.19 (0.02-0.36)], total-to-HDL cholesterol ratio [0.07 (0.04-0.10) and 0.05 (0.02-0.09)], and body mass index [0.14 (0.12-0.17) and 0.07 (0.04-0.10)]. CONCLUSION: We estimated age- and sex-specific percentiles of CCIMT in a healthy population and assessed the association of CV-RFs with CCIMT Z-scores, which enables comparison of IMT values for (patient) groups with different cardiovascular risk profiles, helping interpretation of such measures obtained both in research and clinical settings.
Authors: Yanina Zócalo; Santiago Curcio; Victoria García-Espinosa; Pedro Chiesa; Gustavo Giachetto; Daniel Bia Journal: High Blood Press Cardiovasc Prev Date: 2017-09-25
Authors: Pierleone Lucatelli; Corrado Fagnani; Adam Domonkos Tarnoki; David Laszlo Tarnoki; Beatrice Sacconi; Bence Fejer; Maria Antonietta Stazi; Miriam Salemi; Carlo Cirelli; Alessandro d'Adamo; Fabrizio Fanelli; Carlo Catalano; Pal Maurovich-Horvat; Adam L Jermendy; Gyorgy Jermendy; Bela Merkely; Andrea A Molnar; Giacomo Pucci; Giuseppe Schillaci; Filippo Farina; Giorgio Meneghetti; Claudio Baracchini; Emanuela Medda Journal: Int J Cardiovasc Imaging Date: 2017-10-11 Impact factor: 2.357
Authors: Inge C L van den Munckhof; Helen Jones; Maria T E Hopman; Jacqueline de Graaf; Jean Nyakayiru; Bart van Dijk; Thijs M H Eijsvogels; Dick H J Thijssen Journal: Clin Cardiol Date: 2018-05-12 Impact factor: 2.882
Authors: Francesco Stea; Francesco Faita; Andrea Borghini; Francesca Faita; Fabrizio Bianchi; Elisa Bustaffa; Fabrizio Minichilli; Maria Grazia Andreassi; Rosa Sicari Journal: Environ Sci Pollut Res Int Date: 2016-07-23 Impact factor: 4.223
Authors: Ronnie Ramadan; Saurabh S Dhawan; José Nilo G Binongo; Ayman Alkhoder; Dean P Jones; John N Oshinski; Arshed A Quyyumi Journal: Am Heart J Date: 2016-01-18 Impact factor: 4.749