BACKGROUND AND PURPOSE: We determined the contribution of common carotid intima-media thickness (IMT) in the prediction of future coronary heart disease and cerebrovascular disease when added to established risk factors. METHODS: We used data from a nested case-control study comprising 374 subjects with either an incident stroke or a myocardial infarction and 1496 controls. All subjects were aged 55 years and older and participated in the Rotterdam Study. Mean follow-up was 4.2 years (range, 0.1 to 6.5 years). We evaluated which correlates of coronary heart disease and cerebrovascular disease contribute to the prediction of either a new incident myocardial infarction or a stroke. Logistic regression modeling and the area under the receiver operating characteristic curve (ROC area) were used to quantify the predictive value of the established risk factors and the added value of IMT. RESULTS: The ROC area of a model with age and sex only was 0.65 (95% CI, 0.62 to 0.69). Independent risk factors were previous myocardial infarction and stroke, diabetes mellitus, smoking, systolic blood pressure, diastolic blood pressure, and total and HDL cholesterol levels. These risk factors increased the ROC area from 0.65 to 0.72 (95% CI, 0.69 to 0.75). This model correctly predicted 17% of all subjects with coronary heart disease and cerebrovascular disease. When common carotid IMT was added to the previous model, the ROC area increased to 0.75 (95% CI, 0.72 to 0.78). When only the IMT measurement was used, the ROC area was 0.71 (95% CI, 0.68 to 0.74), and 14% of all subjects were correctly predicted. There was no difference in ROC area when different measurement sites were used. CONCLUSIONS: Adding IMT to a risk function for coronary heart disease and cerebrovascular disease does not result in a substantial increase in the predictive value when used as a screening tool.
BACKGROUND AND PURPOSE: We determined the contribution of common carotid intima-media thickness (IMT) in the prediction of future coronary heart disease and cerebrovascular disease when added to established risk factors. METHODS: We used data from a nested case-control study comprising 374 subjects with either an incident stroke or a myocardial infarction and 1496 controls. All subjects were aged 55 years and older and participated in the Rotterdam Study. Mean follow-up was 4.2 years (range, 0.1 to 6.5 years). We evaluated which correlates of coronary heart disease and cerebrovascular disease contribute to the prediction of either a new incident myocardial infarction or a stroke. Logistic regression modeling and the area under the receiver operating characteristic curve (ROC area) were used to quantify the predictive value of the established risk factors and the added value of IMT. RESULTS: The ROC area of a model with age and sex only was 0.65 (95% CI, 0.62 to 0.69). Independent risk factors were previous myocardial infarction and stroke, diabetes mellitus, smoking, systolic blood pressure, diastolic blood pressure, and total and HDL cholesterol levels. These risk factors increased the ROC area from 0.65 to 0.72 (95% CI, 0.69 to 0.75). This model correctly predicted 17% of all subjects with coronary heart disease and cerebrovascular disease. When common carotid IMT was added to the previous model, the ROC area increased to 0.75 (95% CI, 0.72 to 0.78). When only the IMT measurement was used, the ROC area was 0.71 (95% CI, 0.68 to 0.74), and 14% of all subjects were correctly predicted. There was no difference in ROC area when different measurement sites were used. CONCLUSIONS: Adding IMT to a risk function for coronary heart disease and cerebrovascular disease does not result in a substantial increase in the predictive value when used as a screening tool.
Authors: Mary J Roman; Jorge R Kizer; Lyle G Best; Elisa T Lee; Barbara V Howard; Nawar M Shara; Richard B Devereux Journal: Hypertension Date: 2011-11-07 Impact factor: 10.190
Authors: Patrick Yerly; Nicolas Rodondi; Barathi Viswanathan; Walter Riesen; Pierre Vogt; Pascal Bovet Journal: Int J Cardiovasc Imaging Date: 2012-09-27 Impact factor: 2.357
Authors: Juho R H Raiko; Costan G Magnussen; Mika Kivimäki; Leena Taittonen; Tomi Laitinen; Mika Kähönen; Nina Hutri-Kähönen; Antti Jula; Britt-Marie Loo; Russell J Thomson; Terho Lehtimäki; Jorma S A Viikari; Olli T Raitakari; Markus Juonala Journal: Eur J Cardiovasc Prev Rehabil Date: 2010-10
Authors: Paul P Connell; Pearse A Keane; Evelyn C O'Neill; Rasha W Altaie; Edward Loane; Kumari Neelam; John M Nolan; Stephen Beatty Journal: J Ophthalmol Date: 2009-09-06 Impact factor: 1.909