期刊论文详细信息
BMC Cardiovascular Disorders
A six question screen to facilitate primary cardiovascular disease prevention
Bert-Jan H. van den Born3  Roderik A. Kraaijenhagen1  Lex Burdorf2  Erik S. G. Stroes3  Maurice A. J. Niessen1  Niels V. van der Hoeven1 
[1]NIPED Research Foundation, Amsterdam, The Netherlands
[2]Department of Public Health, Erasmus MC, Rotterdam, The Netherlands
[3]Departments of Internal and Vascular Medicine, Academic Medical Center of the University of Amsterdam, Meibergdreef 9, Amsterdam, 1105AZ, The Netherlands
关键词: SCORE;    Risk management;    Risk assessment;    Risk prediction;    Prevention;    Cardiovascular disease;   
Others  :  1230855
DOI  :  10.1186/s12872-015-0131-0
 received in 2015-06-26, accepted in 2015-10-20,  发布年份 2015
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【 摘 要 】

Background

European guidelines on primary prevention of cardiovascular disease (CVD) recommend the SCORE risk charts for determining CVD risk, which include blood pressure and serum cholesterol as risk parameters. To facilitate cost-effective large-scale screening, we aimed to construct a risk score with ‘non-invasive’ parameters as a first screening step to identify persons at increased CVD risk requiring further risk assessment.

Methods

We used data of Dutch employees from 25 organisations participating in a health risk assessment between August 2007 and January 2013. Backward multivariate logistic regression analysis was employed to select non-invasive, independent predictors of high CVD risk, defined as the 10-year risk of fatal CVD of ≥5 % based on the SCORE formula. The total CVD risk score was calculated as the summed coefficients of the retained variables.

Results

Data of 6189 male participants was used for the development and validation of the risk score. Age, tobacco use, history of hypertension, alcohol consumption, BMI, and waist circumference were independent predictors of high CVD risk. Ten-fold cross-validation resulted in an area under the curve of 0.95 (SE 0.01, 95 % confidence interval 0.94–0.96). A cut-off score ≥45 on the CVD risk score yielded a sensitivity of 0.93, and a specificity of 0.85.

Conclusions

We developed a simple, non-invasive risk score that accurately identifies persons at increased CVD risk according to the SCORE formula in a population of working men. The risk score enables a stepwise approach in large screening programmes, strongly reducing the number of persons that require full risk estimation including blood pressure and cholesterol measures.

【 授权许可】

   
2015 van der Hoeven et al.

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【 参考文献 】
  • [1]European Heart Network: European Cardiovascular Disease Statistics. 2008 edition. 2012.
  • [2]Levi F, Chatenoud L, Bertuccio P, Lucchini F, Negri E, La VC: Mortality from cardiovascular and cerebrovascular diseases in Europe and other areas of the world: an update. Eur J Cardiovasc Prev Rehabil 2009, 16(3):333-350.
  • [3]Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al.: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet 2004, 364(9438):937-952.
  • [4]Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, et al. European Guidelines on cardiovascular disease prevention in clinical practice (version 2012): the Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts). Eur J Prev Cardiol. 2012; 19(4):585–667.
  • [5]Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De BG, et al.: Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003, 24(11):987-1003.
  • [6]Reiner Z, Catapano AL, De BG, Graham I, Taskinen MR, Wiklund O, et al.: ESC/EAS Guidelines for the management of dyslipidaemias: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Eur Heart J 2011, 32(14):1769-1818.
  • [7]Graham IM, Stewart M, Hertog MG: Factors impeding the implementation of cardiovascular prevention guidelines: findings from a survey conducted by the European Society of Cardiology. Eur J Cardiovasc Prev Rehabil 2006, 13(5):839-845.
  • [8]Lindstrom J, Tuomilehto J: The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003, 26(3):725-731.
  • [9]Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, et al.: Identifying individuals at high risk for diabetes: The Atherosclerosis Risk in Communities study. Diabetes Care 2005, 28(8):2013-2018.
  • [10]Schulze MB, Hoffmann K, Boeing H, Linseisen J, Rohrmann S, Mohlig M, et al.: An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care 2007, 30(3):510-515.
  • [11]Kshirsagar AV, Bang H, Bomback AS, Vupputuri S, Shoham DA, Kern LM, et al.: A simple algorithm to predict incident kidney disease. Arch Intern Med 2008, 168(22):2466-2473.
  • [12]Alssema M, Newson RS, Bakker SJ, Stehouwer CD, Heymans MW, Nijpels G, et al.: One risk assessment tool for cardiovascular disease, type 2 diabetes, and chronic kidney disease. Diabetes Care 2012, 35(4):741-748.
  • [13]Niessen MAJ, Kraaijenhagen RA, Dijkgraaf MG, Van PD, Van Kalken CK, Peek N: Impact of a Web-based worksite health promotion program on absenteeism. J Occup Environ Med 2012, 54(4):404-408.
  • [14]Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF III, Feldman HI, et al.: A new equation to estimate glomerular filtration rate. Ann Intern Med 2009, 150(9):604-612.
  • [15]Fayers PM, Sprangers MA: Understanding self-rated health. Lancet 2002, 359(9302):187-188.
  • [16]Mavaddat N, Kinmonth AL, Sanderson S, Surtees P, Bingham S, Khaw KT: What determines Self-Rated Health (SRH)? A cross-sectional study of SF-36 health domains in the EPIC-Norfolk cohort. J Epidemiol Community Health 2011, 65(9):800-806.
  • [17]Rosengren A, Hawken S, Ounpuu S, Sliwa K, Zubaid M, Almahmeed WA, et al.: Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): case–control study. Lancet 2004, 364(9438):953-962.
  • [18]Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al.: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003, 35(8):1381-1395.
  • [19]Donker T, Comijs H, Cuijpers P, Terluin B, Nolen W, Zitman F, et al.: The validity of the Dutch K10 and extended K10 screening scales for depressive and anxiety disorders. Psychiatry Res 2010, 176(1):45-50.
  • [20]Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, et al.: Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med 2002, 32(6):959-976.
  • [21]Means-Christensen AJ, Arnau RC, Tonidandel AM, Bramson R, Meagher MW: An efficient method of identifying major depression and panic disorder in primary care. J Behav Med 2005, 28(6):565-572.
  • [22]Refaeilzadeh P, Tang L, Liu H: Cross-Validation. In Encyclopedia of Database Systems Edited by Liu L, Ozsu MT. 2009, 532-538.
  • [23]Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD: Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001, 54(8):774-781.
  • [24]Bagley SC, White H, Golomb BA: Logistic regression in the medical literature: standards for use and reporting, with particular attention to one medical domain. J Clin Epidemiol 2001, 54(10):979-985.
  • [25]Eckel RH, Grundy SM, Zimmet PZ: The metabolic syndrome. Lancet 2005, 365(9468):1415-1428.
  • [26]Freiberg MS, Cabral HJ, Heeren TC, Vasan RS, Curtis ER: Alcohol consumption and the prevalence of the Metabolic Syndrome in the US.: a cross-sectional analysis of data from the Third National Health and Nutrition Examination Survey. Diabetes Care 2004, 27(12):2954-2959.
  • [27]Puddey IB, Beilin LJ, Rakie V: Alcohol, hypertension and the cardiovascular system: a critical appraisal. Addicition Biol 1997, 2(2):159-170.
  • [28]Van Dis I, Kromhout D, Geleijnse JM, Boer JM, Verschuren WM. Evaluation of cardiovascular risk predicted by different SCORE equations: the Netherlands as an example. Eur J Cardiovasc Prev Rehabil 2010;17:244-249.
  • [29]Niessen MA, Laan EL, Robroek SJ, Essink-Bot ML, Peek N, Kraaijenhagen RA, et al.: Determinants of participation in a web-based health risk assessment and consequences for health promotion programs. J Med Internet Res 2013, 15(8):e151.
  • [30]Warren TY, Barry V, Hooker SP, Sui X, Church TS, Blair SN: Sedentary behaviors increase risk of cardiovascular disease mortality in men. Med Sci Sports Exerc 2010, 42(5):879-885.
  • [31]Nyholm M, Gullberg B, Merlo J, Lundqvist-Persson C, Rastam L, Lindblad U: The validity of obesity based on self-reported weight and height: Implications for population studies. Obesity (Silver Spring) 2007, 15(1):197-208.
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