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Prediction of stroke in the general population in Europe (EUROSTROKE): Is there a role for fibrinogen and electrocardiography?
  1. K G M Moons1,
  2. M L Bots1,2,
  3. J T Salonen3,
  4. P C Elwood4,
  5. A Freire de Concalves5,
  6. Y Nikitin6,
  7. J Sivenius7,
  8. D Inzitari8,
  9. V Benetou9,
  10. J Tuomilehto10,
  11. P J Koudstaal11,
  12. D E Grobbee1,2
  1. 1Julius Centre for General Practice and Patient Oriented Research, University Medical Centre Utrecht, the Netherlands
  2. 2Epidemiology and Biostatistics, Erasmus University Medical School, Rotterdam, the Netherlands
  3. 3Research Institute of Public Health, University of Kuopio, Kuopio, Finland
  4. 4MRC Epidemiology Unit, Llandough Hospital, Penarth, South Glamorgan, UK
  5. 5Neurology, Hospitais da Universidade de Coimbra, Coimbra, Portugal
  6. 6Russian Academy of Medical Sciences Siberian Branch, Institute of Internal Medicine, Novosibirsk, Russia
  7. 7Department of Neurology, University of Kuopio, Kuopio, Finland
  8. 8Neurological and Psychiatric Sciences, University of Florence, Florence, Italy
  9. 9Hygiene and Epidemiology, University of Athens Medical School, Athens, Greece
  10. 10Epidemiology and Health Promotion, National Public Health Institute, Helsinki, Finland
  11. 11Neurology, University Hospital Rotterdam Dijkzigt, Rotterdam, the Netherlands
  1. Correspondence to:
 Dr M L Bots, Julius Centre for General Practice and Patient Oriented Research, University Medical Centre Utrecht, room D01.335, PO Box 85500, 3508 GA Utrecht, the Netherlands;
 M.L.Bots{at}jc.azu.nl

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.

  • cohort
  • prediction
  • stroke, cardiovascular disease
  • MI, myocardial infarction
  • LVH, left ventricular hypertrophy
  • MEANS, Means Electrocardiogram Analysis System

https://doi.org/10.1136/jech.56.suppl_1.i30

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    Footnotes

    • Funding: EUROSTROKE is supported by grant BMH1-CT93–1786 from the European Community BIOMED I programme and by grant CIPD-CT94–0256 from the European Community PECO programme.