A model for predicting the risk of carotid artery disease.

OBJECTIVE: To develop a model for the identification of individuals at risk for carotid stenosis (CS) that could be useful in a clinical setting when trying to decide whether screening is worthwhile. BACKGROUND: Evidence that aggressive medical therapy and life style changes reduce the risk of stroke in individuals with CS is increasing and has led to a renewed interest in screening for CS. METHODS: Data on demographics and risk factors were obtained from 2,885,257 individuals who had carotid Duplex scans by Life Line Screening between 2003 and 2008. Multivariable logistic regression analysis was used to identify independent risk factors for CS (>50% stenosis). A scoring system was developed where risk factors were assigned a weighted score. Predictive ability was assessed by calculating C statistics and r2. RESULTS: In the screened cohort, 71,004 patients (2.4%) had CS. Independent risk factors include advanced age, smoking, peripheral arterial disease, high blood pressure, coronary artery disease, diabetes, cholesterol, and abdominal aortic aneurysm. African Americans, Asians, and Hispanics had reduced risk than whites. Exercise and consumption of fruit, vegetables, and nuts had a modest protective effect. A predictive scoring system was created that identifies individuals with CS more efficiently (C statistic = 0.753) than previously published models. CONCLUSIONS: We provide a model that enables identification of individuals who have a high probability of having CS. This model can be helpful in designing targeted screening programs that are cost-effective.

Development of a novel scoring tool for the identification of large ≥5 cm abdominal aortic aneurysms.

OBJECTIVE: Current screening recommendations for abdominal aortic aneurysm (AAA) target >3-cm diameter aneurysms in ever-smoking 65- to 75-year-old males. However, more than 50% of AAA ruptures occur in individuals outside this patient cohort, and only a subset of AAAs detected are large enough to warrant surgery. In this analysis, we evaluated more than 3 million screened individuals and developed a scoring tool to identify ≥5-cm diameter AAAs in the entire population at risk. METHODS: Between 2003 and 2008, demographics and risk factors were collected from 3.1 million people undergoing ultrasound screening for AAA by Life Line Screening, Inc. Using multivariable logistic regression analysis, we identified risk factors and developed a scoring system to predict the presence of ≥5-cm diameter AAAs. RESULTS: Smoking had a profound influence on the risk of AAA, which increased with number of cigarettes smoked and years of smoking, and decreased following smoking cessation. Novel findings included a protective effect of exercise, normal weight, and Black/Hispanic race/ethnicity. Using these and other factors, the scoring system provided good predictive accuracy (C-statistic = 0.82), when tested against the validation subset of the study cohort. The model predicts the presence of 121,000 ≥5 cm AAA in the US population (prevalence: 0.14%). Demonstrating the inadequacy of the current screening recommendations, only 35% of these aneurysms were among males aged 65 to 75 years. CONCLUSIONS: Based on the largest cohort of patients ever screened for AAA, we developed a screening strategy that can identify large AAAs in a broad population of individuals at risk.

Analysis of risk factors for abdominal aortic aneurysm in a cohort of more than 3 million individuals.

BACKGROUND: Abdominal aortic aneurysm (AAA) disease is an insidious condition with an 85% chance of death after rupture. Ultrasound screening can reduce mortality, but its use is advocated only for a limited subset of the population at risk. METHODS: We used data from a retrospective cohort of 3.1 million patients who completed a medical and lifestyle questionnaire and were evaluated by ultrasound imaging for the presence of AAA by Life Line Screening in 2003 to 2008. Risk factors associated with AAA were identified using multivariable logistic regression analysis. RESULTS: We observed a positive association with increasing years of smoking and cigarettes smoked and a negative association with smoking cessation. Excess weight was associated with increased risk, whereas exercise and consumption of nuts, vegetables, and fruits were associated with reduced risk. Blacks, Hispanics, and Asians had lower risk of AAA than whites and Native Americans. Well-known risk factors were reaffirmed, including male gender, age, family history, and cardiovascular disease. A predictive scoring system was created that identifies aneurysms more efficiently than current criteria and includes women, nonsmokers, and individuals aged <65 years. Using this model on national statistics of risk factors prevalence, we estimated 1.1 million AAAs in the United States, of which 569,000 are among women, nonsmokers, and individuals aged <65 years. CONCLUSIONS: Smoking cessation and a healthy lifestyle are associated with lower risk of AAA. We estimated that about half of the patients with AAA disease are not eligible for screening under current guidelines. We have created a high-yield screening algorithm that expands the target population for screening by including at-risk individuals not identified with existing screening criteria.