Abstract
Stroke is a common condition with a substantial impact on health care. Using published epidemiological data, a mathematical model was created to predict annual stroke incidence in populations over 45 years old, utilizing age, gender, ethnicity, and stroke risk factor prevalence (hypertension, atrial fibrillation, diabetes, smoking, and ischemic heart disease). The purpose of this study is to assess the models ability to reliably estimate the annual number of first strokes. The model was validated against two cohorts: the Northern Manhattan Stroke Study (NM), performed in 1995 and 1996, and the Copenhagen City Heart Study (CCHS), undertaken in 1980-84, 1984-88, and 1988-93. Both cohorts provided the actual number of first strokes for respective years and risk factor prevalence. The Mantel-Haenszel test compared actual to predicted incidence rates. The two cohorts differed in risk factor prevalences, size, and demographics. For all cohort groups/years, the predicted number of annual first strokes was not statistically different from actual first stroke incidence (P >.05). In NM, the actual number of first strokes compared to predicted was 7 versus 13 (P =.18) for 1995 and 9 versus 18 (P =.08) for 1996. Actual and predicted annual strokes in CCHS for the time frames 1980-83, 1984-88, and 1988-93 were 65 versus 69 (P =.73), 72 versus 87 (P =.23), and 75 versus 93 (P =.16), respectively. The model provides a tool for estimating annual first strokes within a population, with a tendency of bias toward overestimating the number of incident strokes. This evidence-based model may be utilized by health policy makers to predict stroke burden at a population level. Copyright © 2003 by National Stroke Association