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Logo of jepicomhInstructions for authorsCurrent TOCJournal of Epidemiology and Community Health
 
J Epidemiol Community Health. Feb 2002; 56(Suppl 1): i30–i36.
PMCID: PMC1765507
Prediction of stroke in the general population in Europe (EUROSTROKE): Is there a role for fibrinogen and electrocardiography?
K Moons, M Bots, J Salonen, P Elwood, d Freire, Y Nikitin, J Sivenius, D Inzitari, V Benetou, J Tuomilehto, P Koudstaal, and D Grobbee
Abstract
Background: To decide whether a person with certain characteristics should be given any kind of intervention to prevent a cardiovascular event, it would be helpful to classify subjects in low, medium and high risk categories. The study evaluated which well known cerebrovascular and cardiovascular correlates, in particular fibrinogen level and ECG characteristics, are able to predict the occurrence of stroke in men of the general population using data from three European cohorts participating in EUROSTROKE.
Methods: EUROSTROKE is a collaborative project among ongoing European population based cohort studies and designed as a prospective nested case-control study. For each stroke case two controls were sampled. Strokes were classified according to MONICA criteria or reviewed by a panel of four neurologists. Complete data were available of 698 men (219 stroke events) from cohorts in Cardiff (84 cases/200 controls), Kuopio (74/148) and Rotterdam (61/131). Multivariable logistic regression modeling was used to evaluate which information from history, physical examination (for example, blood pressure), blood lipids, and fibrinogen and ECG measurements independently contributed to the prediction of stroke. The area under receiver operating characteristic curve (ROC area) was used to estimate the predictive ability of models.
Results: Independent predictors from medical history and physical examination were age, stroke history, medically treated hypertension, smoking, diabetes mellitus and diastolic blood pressure. The ROC area of this model was 0.69. After validating and transforming this model to an easy applicable rule, 40% of all future stroke cases could be predicted. Adding pulse rate, body mass index, blood lipids, fibrinogen level and ECG parameters did not improve the classification of subjects in low, medium and high risk. Results were similar when fibrinogen was dichotomised at the upper tertile or quintile.
Conclusion: In the general male population the future occurrence of stroke may be predicted using easy obtainable information from medical history and physical examination. Measurement of pulse rate, body mass index, blood lipids, fibrinogen level and ECG characteristics do not contribute to the risk stratification of stroke and have no value in the screening for stroke in the general male population.
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