Skip to main navigation menu Skip to main content Skip to site footer

Original article

Vol. 145 No. 3738 (2015)

Impact of risk factors on cardiovascular risk: a perspective on risk estimation in a Swiss population

  • Sigrun A. Chrubasik
  • Cosima A. Chrubasik
  • Jörg Piper
  • Juergen Schulte-Moenting
  • Paul Erne
Cite this as:
Swiss Med Wkly. 2015;145:w14180


INTRODUCTION: In models and scores for estimating cardiovascular risk (CVR), the relative weightings given to blood pressure measurements (BPMs), and biometric and laboratory variables are such that even large differences in blood pressure lead to rather low differences in the resulting total risk when compared with other concurrent risk factors. We evaluated this phenomenon based on the PROCAM score, using BPMs made by volunteer subjects at home (HBPMs) and automated ambulatory BPMs (ABPMs) carried out in the same subjects.

METHODS: A total of 153 volunteers provided the data needed to estimate their CVR by means of the PROCAM formula. Differences (deltaCVR) between the risk estimated by entering the ABPM and that estimated with the HBPM were compared with the differences (deltaBPM) between the ABPM and the corresponding HBPM. In addition to the median values (= second quartile), the first and third quartiles of blood pressure profiles were also considered. PROCAM risk values were converted to European Society of Cardiology (ESC) risk values and all participants were assigned to the risk groups low, medium and high.

RESULTS: Based on the PROCAM score, 132 participants had a low risk for suffering myocardial infarction, 16 a medium risk and 5 a high risk. The calculated ESC scores classified 125 participants into the low-risk group, 26 into the medium- and 2 into the high-risk group for death from a cardiovascular event. Mean ABPM tended to be higher than mean HBPM. Use of mean systolic ABPM or HBPM in the PROCAM formula had no major impact on the risk level.

CONCLUSIONS: Our observations are in agreement with the rather low weighting of blood pressure as risk determinant in the PROCAM score. BPMs assessed with different methods had relatively little impact on estimation of cardiovascular risk in the given context of other important determinants. The risk calculations in our unselected population reflect the given classification of Switzerland as a so-called cardiovascular “low risk country”.


  1. National Heart Lung, and Blood Institute, National Institute of Health. Framingham Heart Study. 2002.
  2. Schulte H, Cullen P, Assmann G. Obesity, mortality and cardiovascular disease in the Münster Heart Study (PROCAM). Atherosclerosis. 1999;144:199–209.
  3. Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the Prospective Cardiovascular Münster (PROCAM) Study. Circulation. 2002;105:310–5.
  4. Assmann G, Schulte H, Cullen P, Seedorf U. Assessing risk of myocardial infarction and stroke: new data from the Prospective Cardiovascular Münster (PROCAM) Study. Eur J Clin Invest. 2007;37:925–32.
  5. International Task Force for Prevention of Coronary Heart Disease. Procam Risik Calculator. 2005.
  6. Kromhout D, Menotti A, Blackburn H (Eds). Prevention of coronary heart disease. Diet, lifestyle and risk factors in the Seven Countries Study. Kluwer Academic Publishers, Boston, 2002.
  7. Conroy RM, Pyörälä K, Fitzgerald AP, et al., on behalf of the SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Result of a risk estimation study in Europe. Eur Heart J. 2003;24:987–1003.
  8. European Society of Cardiology. Heartscore: the interactive tool for predicting and managing the risk of heart attack and stroke in Europe. 2005.
  9. Giampaoli S, Palmieri L, Mattiello A, Panico S. Definition of high risk individuals to optimise strategies for primary prevention of cardiovascular diseases. Nutr Metab Cardiovasc Dis. 2005;15:79–85.
  10. Piper J. Kardiovaskuläre Risikostratifizierung in der Primärprävention Teil 1: Möglichkeiten und Grenzen etablierter Risiko-Scores. Präv.-Rehab. 2006;18:1–7. German.
  11. Swiss Atherosclerosis Association, Arbeitsgruppe Lipide und Atherosklerose (AGLA): AGLA-Risikorechner. German.
  12. Warren RE, Marshall T, Padfield PE, Chrubasik S. Variability of office, 24-hour ambulatory, and self-monitored blood pressure measurements. Br J Gen Pract. 2010;60:675–80.
  13. Bliziotis IA, Destounis A, Stergiou GS. Home versus ambulatory and office blood pressure in predicting target organ damage in hypertension: a systematic review and meta-analysis. J Hypertens. 2012;30:1289–99.
  14. Gaborieau V, Delarche N, Gosse P. Ambulatory blood pressure monitoring versus self-measurement of blood pressure at home: correlation with target organ damage. J Hypertens. 2008;26:1919–27.
  15. Chrubasik-Hausmann S, Chrubasik C, Walz S, Schulte Mönting J, Erne P. Comparison of home and daytime ambulatory blood pressure measurements. Cardiovascular Disorders. 2014;14:94.
  16. Hodgkinson J, Mant J, Martin U, Guo B, Hobbs FD, Deeks JJ, et al. Relative effectiveness of clinic and home blood pressure monitoring compared with ambulatory blood pressure monitoring in diagnosis of hypertension: systematic review. BM. 2011;342:d3621.
  17. Meurer, KA, Wambach G, Petri E, Deter H Ch. Arterielle Hypertonie (konsetrvative Behandlung). In: Bünte et al. (Edts.): Therapie-Handbuch. Urban & Scharzenberg, München, 1997.
  18. Piper J. Kardiovaskuläre Risikostratifizierung in der Primärprävention Teil 2: Neue Aspekte einer erweiterten individuellen Risikoerfassung. Präv-Rehab. 2006;18:8–21.
  19. Piper J. Kardiovaskuläre Risikostratifizierung in der Primärprävention Teil 3: Mathematische Modelle zur Relativität von Risikofaktoren und Risiko-Scores. Präv-Rehab. 2006;18:22–8.
  20. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al.; INTERHEART Study Investigators. Effect of protencially modificable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): chase control study. Lancet. 2004;364:937–52.
  21. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al.; INTERHEART Study Investigators. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005;366:1640–9.
  22. Palatini P. Ambulatory and home blood pressure measurement: complementary rather than competitive methods. Hypertension. 2012;59:2–4.

Most read articles by the same author(s)

<< < 1 2