Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Cystatin C as a predictor of cardiovascular outcomes in a hypertensive population

Journal of Human Hypertension volume 31, pages 801–807 (2017)Cite this article

Subjects

Abstract

Calculating the estimated glomerular filtration rate (eGFR) using creatinine-based equations may underestimate cardiovascular risk. Cystatin C-based eGFR may be a stronger prognostic biomarker than creatinine-based eGFR when assessing cardiovascular outcomes and mortality. Our aim was to determine whether levels of serum cystatin C, as an estimator of GFR, had a higher predictive value than creatinine-based eGFR for incident cardiovascular disease among hypertensive patients. We retrospectively analyzed the records of 2016 hypertensive patients from the Hypertension Unit at Mostoles University Hospital between 2006 and 2016. We calculated the eGFR using 3 CKD-EPI equations. The outcomes we included in our study were cardiovascular death, non-cardiovascular death, stroke, incident heart failure, and myocardial infarction. We used the Cox regression hazard model to estimate the hazard ratio. Our analysis found that, in terms of cardiovascular morbidity and mortality, both cystatin C-based eGFR (HR 2.88, 95% CI 1.86–4.47, P<0.0001) showed a higher prognostic value than creatinine-based eGFR (HR 2.83, 95% CI 1.73–4.63, P<0.0001). In terms of all-cause mortality, cystatin C-based eGFR (HR 4.24, 95% CI 2.38–7.53, P<0.0001) showed a higher prognostic value than creatinine-based eGFR (HR 2.77, 95% CI 1.43–5.36, P<0.0001). Our findings suggest that both cystatin C-based eGFRs may be stronger predictors of all-cause mortality and cardiovascular events in our hypertensive cohort when compared to creatinine-based eGFR, and may improve the risk assessment in certain populations.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

References

  1. Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS et al. Global prevalence of chronic kidney disease–a systematic review and meta-analysis. PLoS ONE 2016; 11: e0158765.

    Article  Google Scholar 

  2. O’Callaghan CA, Shine B, Lasserson DS . Chronic kidney disease: a large-scale population-based study of the effects of introducing the CKD-EPI formula for eGFR reporting. BMJ Open 2011; 1: e000308.

    PubMed  PubMed Central  Google Scholar 

  3. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu C . Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004; 351: 1296–1305.

    Article  CAS  Google Scholar 

  4. Sarnak MJ, Levey AS, Schoolwerth AC, Coresh J, Culleton B, Hamm LL et al. Kidney disease as a risk factor for development of cardiovascular disease. Circulation 2003; 108: 2154–2169.

    Article  Google Scholar 

  5. Stevens PE, Levin A . Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med 2013; 158: 825–830.

    Article  Google Scholar 

  6. KDIGO. 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013; 3: 1–150.

    Article  Google Scholar 

  7. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150: 604–612.

    Article  Google Scholar 

  8. Rule AD, Larson TS, Bergstralh EJ, Slezak JM, Jacobsen SJ, Cosio FG . Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Ann Intern Med 2004; 141: 929–937.

    Article  CAS  Google Scholar 

  9. Wu C-K, Lin J-W, Caffrey JL, Chang M-H, Hwang J-J, Lin Y-S, . Cystatin C and long-term mortality among subjects with normal creatinine-based estimated glomerular filtration rates: NHANES III (Third National Health and Nutrition Examination Survey). J Am Coll Cardiol 2010; 56: 1930–1936.

    Article  CAS  Google Scholar 

  10. Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR et al. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med 2013; 369: 932–943.

    Article  CAS  Google Scholar 

  11. Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010; 375: 2073–2081.

    Article  Google Scholar 

  12. Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med 2005; 352: 2049–2060.

    Article  CAS  Google Scholar 

  13. Menon V, Shlipak MG, Wang X, Coresh J, Greene T, Stevens L et al. Cystatin C as a risk factor for outcomes in chronic kidney disease. Ann Intern Med Am 2007; 147: 19–27.

    Article  Google Scholar 

  14. Lackland DT, Weber MA . Global burden of cardiovascular disease and stroke: hypertension at the core. Can J Cardiol 2015; 31: 569–571.

    Article  Google Scholar 

  15. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med Mass Medical Soc 2012; 367: 20–29.

    Article  CAS  Google Scholar 

  16. Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014; 63: 713–735.

    Article  Google Scholar 

  17. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria, 2016.

  18. Pattaro C. nephro: Biostatistics Utilities for Nephrology, 2015.

  19. Kundu S, Aulchenko YS, Janssens ACJW . PredictABEL: Assessment of Risk Prediction Models, 2014.

  20. Astor BC, Levey AS, Stevens LA, Van Lente F, Selvin E, Coresh J . Method of glomerular filtration rate estimation affects prediction of mortality risk. J Am Soc Nephrol 2009; 20: 2214–2222.

    Article  Google Scholar 

  21. Van Biesen W, De Bacquer D, Verbeke F, Delanghe J, Lameire N, Vanholder R . The glomerular filtration rate in an apparently healthy population and its relation with cardiovascular mortality during 10 years. Eur Heart J 2007; 28: 478–483.

    Article  Google Scholar 

  22. Di Angelantonio E, Chowdhury R, Sarwar N, Aspelund T, Danesh J, Gudnason V . Chronic kidney disease and risk of major cardiovascular disease and non-vascular mortality: prospective population based cohort study. BMJ 2010; 341: c4986.

    Article  Google Scholar 

  23. Mathisen UD, Melsom T, Ingebretsen OC, Jenssen T, Njølstad I, Solbu MD et al. Estimated GFR associates with cardiovascular risk factors independently of measured GFR. J Am Soc Nephrol 2011; 22: 927–937.

    Article  Google Scholar 

  24. Shlipak MG, Katz R, Sarnak MJ, Fried LF, Newman AB, Stehman-Breen C et al. Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease. Ann Intern 2006; 145: 237–246.

    Article  CAS  Google Scholar 

  25. Peralta CA, Katz R, Sarnak MJ, Ix J, Fried LF, De Boer I et al. Cystatin C identifies chronic kidney disease patients at higher risk for complications. J Am Soc Nephrol 2011; 22: 147–155.

    Article  Google Scholar 

  26. Bild DE, Bluemke DA, Burke GL, Detrano R, Roux AVD, Folsom AR et al. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol 2002; 156: 871–881.

    Article  Google Scholar 

  27. Fried LP, Borhani NO, Enright P, Furberg CD, Gardin JM, Kronmal RA et al. The cardiovascular health study: design and rationale. Ann Epidemiol 1991; 1: 263–276.

    Article  CAS  Google Scholar 

  28. Tangri N, Inker LA, Tighiouart H, Sorensen E, Menon V, Beck G et al. Filtration markers may have prognostic value independent of glomerular filtration rate. J Am Soc Nephrol 2012; 23: 351–359.

    Article  CAS  Google Scholar 

  29. Concato J, Peduzzi P, Holford TR, Feinstein AR . Importance of events per independent variable in proportional hazards analysis I. Background, goals, and general strategy. J Clin Epidemiol 1995; 48: 1495–1501.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank Jacqueline Lamb for her invaluable advice and tips for English grammar and spelling, and Blanca San Jose Montano, the Health Science Librarian and Documentalist at our institution, for her great support, suggestions and encouragement in the preparation of this manuscript. This study has been partly funded by Research Projects TEC2016-75361-R and TEC2016-75161-C2-1-4 from the Spanish Government.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Author information

Authors and Affiliations

  1. Department of Internal Medicine, Mostoles University Hospital, Madrid, Spain

    R Garcia-Carretero & L Vigil-Medina

  2. Department of Signal Theory and Communications and Telematics Systems and Computing, Rey Juan Carlos University, Madrid, Spain

    O Barquero-Perez, R Goya-Esteban, I Mora-Jimenez, C Soguero-Ruiz & J Ramos-Lopez

Authors
  1. R Garcia-Carretero
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. L Vigil-Medina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. O Barquero-Perez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. R Goya-Esteban
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. I Mora-Jimenez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C Soguero-Ruiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. J Ramos-Lopez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R Garcia-Carretero.

Ethics declarations

Competing interests

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Garcia-Carretero, R., Vigil-Medina, L., Barquero-Perez, O. et al. Cystatin C as a predictor of cardiovascular outcomes in a hypertensive population. J Hum Hypertens 31, 801–807 (2017). https://doi.org/10.1038/jhh.2017.68

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/jhh.2017.68

This article is cited by

Search

Advanced search

Quick links