BACKGROUND: Carotid intima-media thickness (IMT) is increasingly used as a surrogate marker for atherosclerosis. Its use relies on its ability to predict future clinical cardiovascular end points. We performed a systematic review and meta-analysis of data to examine this association. METHODS AND RESULTS: Using a prespecified search strategy, we identified 8 relevant studies and compared study design, measurement protocols, and reported data. We identified sources of heterogeneity between studies. The assumption of a linear relationship between IMT and risk was challenged by use of a graphical technique. To obtain a pooled estimate of the relative risk per IMT difference, we performed a meta-analysis based on random effects models. The age- and sex-adjusted overall estimates of the relative risk of myocardial infarction were 1.26 (95% CI, 1.21 to 1.30) per 1-standard deviation common carotid artery IMT difference and 1.15 (95% CI, 1.12 to 1.17) per 0.10-mm common carotid artery IMT difference. The age- and sex-adjusted relative risks of stroke were 1.32 (95% CI, 1.27 to 1.38) per 1-standard deviation common carotid artery IMT difference and 1.18 (95% CI, 1.16 to 1.21) per 0.10-mm common carotid artery IMT difference. Major sources of heterogeneity were age distribution, carotid segment definition, and IMT measurement protocol. The relationship between IMT and risk was nonlinear, but the linear models fitted relatively well for moderate to high IMT values. CONCLUSIONS: Carotid IMT is a strong predictor of future vascular events. The relative risk per IMT difference is slightly higher for the end point stroke than for myocardial infarction. In future IMT studies, ultrasound protocols should be aligned with published studies. Data for younger individuals are limited and more studies are required.
BACKGROUND: Carotid intima-media thickness (IMT) is increasingly used as a surrogate marker for atherosclerosis. Its use relies on its ability to predict future clinical cardiovascular end points. We performed a systematic review and meta-analysis of data to examine this association. METHODS AND RESULTS: Using a prespecified search strategy, we identified 8 relevant studies and compared study design, measurement protocols, and reported data. We identified sources of heterogeneity between studies. The assumption of a linear relationship between IMT and risk was challenged by use of a graphical technique. To obtain a pooled estimate of the relative risk per IMT difference, we performed a meta-analysis based on random effects models. The age- and sex-adjusted overall estimates of the relative risk of myocardial infarction were 1.26 (95% CI, 1.21 to 1.30) per 1-standard deviation common carotid artery IMT difference and 1.15 (95% CI, 1.12 to 1.17) per 0.10-mm common carotid artery IMT difference. The age- and sex-adjusted relative risks of stroke were 1.32 (95% CI, 1.27 to 1.38) per 1-standard deviation common carotid artery IMT difference and 1.18 (95% CI, 1.16 to 1.21) per 0.10-mm common carotid artery IMT difference. Major sources of heterogeneity were age distribution, carotid segment definition, and IMT measurement protocol. The relationship between IMT and risk was nonlinear, but the linear models fitted relatively well for moderate to high IMT values. CONCLUSIONS: Carotid IMT is a strong predictor of future vascular events. The relative risk per IMT difference is slightly higher for the end point stroke than for myocardial infarction. In future IMT studies, ultrasound protocols should be aligned with published studies. Data for younger individuals are limited and more studies are required.
Authors: Priscilla Y Hsue; Karen Ordovas; Theodore Lee; Gautham Reddy; Michael Gotway; Amanda Schnell; Jennifer E Ho; Van Selby; Erin Madden; Jeffrey N Martin; Steven G Deeks; Peter Ganz; David D Waters Journal: Am J Cardiol Date: 2011-12-09 Impact factor: 2.778
Authors: Natalia D Gavriliuk; Tatiana A Druzhkova; Olga B Irtyuga; Alexandr A Zhloba; Tatiana F Subbotina; Vladimir E Uspenskiy; Nina P Alexeyeva; Olga M Moiseeva Journal: Aorta (Stamford) Date: 2016-12-01
Authors: Jonathan Rubin; Vijay Nambi; Lloyd E Chambless; Michael W Steffes; Stephen P Juraschek; Josef Coresh; A Richey Sharrett; Elizabeth Selvin Journal: Atherosclerosis Date: 2012-09-13 Impact factor: 5.162
Authors: Eric B Loucks; Shelley E Taylor; Joseph F Polak; Aude Wilhelm; Preety Kalra; Karen A Matthews Journal: Soc Sci Med Date: 2013-12-19 Impact factor: 4.634
Authors: Alain G Bertoni; Melicia C Whitt-Glover; Hyoju Chung; Katherine Y Le; R Graham Barr; Mahadevappa Mahesh; Nancy S Jenny; Gregory L Burke; David R Jacobs Journal: Am J Epidemiol Date: 2008-12-15 Impact factor: 4.897