Skip to main content

Advertisement

SpringerLink
Log in

Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths

  • Ischemic Heart Disease (D Mukherjee, Section Editor)
  • Published:
Current Cardiology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths.

Recent Findings

Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk.

Summary

It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: •• Of major importance

  1. Beswick A, Brindle P. Risk scoring in the assessment of cardiovascular risk. Curr Opin Lipidol. 2006;17:375–86. https://doi.org/10.1097/01.mol.0000236362.56216.44.

    Article  CAS  PubMed  Google Scholar 

  2. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart. 2006;92:1752–9. https://doi.org/10.1136/hrt.2006.087932.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Crowson CS, Atkinson EJ, Therneau TM. Assessing calibration of prognostic risk scores. Stat Methods Med Res. 2016;25(4):1692–706. https://doi.org/10.1177/0962280213497434.

    Article  PubMed  Google Scholar 

  4. Kramer AA, Zimmerman JE. Assessing the calibration of mortality benchmarks in critical care: the Hosmer-Lemeshow test revisited. Crit Care Med. 2007;35:2052–6. https://doi.org/10.1097/01.CCM.0000275267.64078.B0.

    Article  PubMed  Google Scholar 

  5. Vincent JL, Moreno R. Clinical review: scoring systems in the critically ill. Crit Care. 2010;14(2):207. https://doi.org/10.1186/cc8204.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mahmood SS, Levy D, Vasan RS, Wang TJ. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Lancet. 2014;383(9921):999–1008. https://doi.org/10.1016/S0140-6736(13)61752-3.

    Article  PubMed  Google Scholar 

  7. British Cardiac Society. JBS 2: joint British societies’ guidelines on prevention of cardiovascular disease in clinical practice. Heart. 2005;91:v1–52. https://doi.org/10.1136/hrt.2005.079988.

    Article  Google Scholar 

  8. Jackson R. Updated New Zealand cardiovascular disease risk-benefit prediction guide. BMJ. 2000;320:709–10. https://doi.org/10.1136/bmj.320.7236.709.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. D’agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care. Circulation. 2008;117(6):743–53. https://doi.org/10.1161/CIRCULATIONAHA.107.699579.

    Article  PubMed  Google Scholar 

  10. Rabanal KS, Meyer HE, Pylypchuk R, Mehta S, Selmer RM, Jackson RT. Performance of a Framingham cardiovascular risk model among Indians and Europeans in New Zealand and the role of body mass index and social deprivation. Open Heart. 2018;5(2):e000821. https://doi.org/10.1136/openhrt-2018-000821.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Brindle P, Emberson J, Lampe F, Walker M, Whincup P, Fahey T, et al. Predictive accuracy of the Framingham coronary risk score in British men: prospective cohort study. BMJ. 2003;327(7426):1267. https://doi.org/10.1136/bmj.327.7426.1267.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Asia Pacific Cohort Studies Collaboration, Barzi F, Patel A, Gu D, Sritara P, Lam TH, et al. Cardiovascular risk prediction tools for populations in Asia. J Epidemiol Community Health. 2007;61(2):115–21. https://doi.org/10.1136/jech.2005.044842.

  13. Thomsen TF, McGee D, Davidsen M, Jørgensen T. A cross-validation of risk-scores for coronary heart disease mortality based on data from the Glostrup population studies and Framingham Heart Study. Int J Epidemiol. 2002;31(4):817–22. https://doi.org/10.1093/ije/31.4.817.

    Article  PubMed  Google Scholar 

  14. Hense HW, Schulte H, Löwel H, Assmann G, Keil U. Framingham risk function overestimates risk of coronary heart disease in men and women from Germany–results from the MONICA Augsburg and the PROCAM cohorts. Eur Heart J. 2003;24(10):937–45. https://doi.org/10.1016/s0195-668x(03)00081-2.

    Article  PubMed  Google Scholar 

  15. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24(11):987–1003. https://doi.org/10.1016/s0195-668x(03)00114-3.

  16. Thomsen T. HeartScore: a new web-based approach to European cardiovascular disease risk management. Eur J Cardiovasc Prev Rehabil. 2005;12(5):424–6. https://doi.org/10.1097/01.hjr.0000186617.29992.11 (PMID: 16210927).

  17. Courand PY, Lenoir J, Grandjean A, Garcia D, Harbaoui B, Lantelme P. SCORE underestimates cardiovascular mortality in hypertension: insight from the OLD-HTA and NEW-HTA Lyon cohorts. Eur J Prev Cardiol. 2021 Jan 18:zwaa163. https://doi.org/10.1093/eurjpc/zwaa163.

  18. Goh LG, Welborn TA, Dhaliwal SS. Independent external validation of cardiovascular disease mortality in women utilising Framingham and SCORE risk models: a mortality follow-up study. BMC Womens Health. 2014;26(14):118. https://doi.org/10.1186/1472-6874-14-118.

    Article  Google Scholar 

  19. Selvarajah S, Kaur G, Haniff J, Cheong KC, Hiong TG, van der Graaf Y, et al. Comparison of the Framingham risk score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. Int J Cardiol. 2014;176(1):211–8. https://doi.org/10.1016/j.ijcard.2014.07.066.

    Article  PubMed  Google Scholar 

  20. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Gibbons R, et al. American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;129(25 Suppl 2):S49–73. https://doi.org/10.1161/01.cir.0000437741.48606.98.

  21. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. ACC/AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019;2019(74):e177-232. https://doi.org/10.1016/j.jacc.2019.03.010.

    Article  Google Scholar 

  22. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators.Am J Epidemiol. 1989;129:687–702.

  23. 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(3):263–76. https://doi.org/10.1016/1047-2797(91)90005-w.

    Article  CAS  PubMed  Google Scholar 

  24. Friedman GD, Cutter GR, Donahue RP, Hughes GH, Hulley SB, Jacobs DR Jr, et al. CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol. 1988;41(11):1105–16. https://doi.org/10.1016/0895-4356(88)90080-7.

    Article  CAS  PubMed  Google Scholar 

  25. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham offspring study. Am J Epidemiol. 1979;110(3):281–90. https://doi.org/10.1093/oxfordjournals.aje.a112813

  26. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB Sr, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63(25 Pt B):2935–2959. https://doi.org/10.1016/j.jacc.2013.11.005.

  27. Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart disease and stroke statistics—2021 update: a report from the American Heart Association. Circulation. 2021;143(8):e254-743. https://doi.org/10.1161/CIR.0000000000000950.

    Article  PubMed  Google Scholar 

  28. Muntner P, Colantonio LD, Cushman M, Goff DC Jr, Howard G, Howard VJ, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014;311(14):1406–15. https://doi.org/10.1001/jama.2014.2630.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Golabi P, Fukui N, Paik J, Sayiner M, Mishra A, Younossi ZM. Mortality risk detected by atherosclerotic cardiovascular disease score in patients with nonalcoholic fatty liver disease. Hepatol Commun. 2019;3(8):1050–60. https://doi.org/10.1002/hep4.1387.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds risk score. JAMA. 2007;297(6):611–9. https://doi.org/10.1001/jama.297.6.611.

    Article  CAS  PubMed  Google Scholar 

  31. Ambale-Venkatesh B, Yang X, Wu CO, Liu K, Hundley WG, McClelland R, et al. Cardiovascular event prediction by machine learning: the multi-ethnic study of atherosclerosis. Circ Res. 2017;121(9):1092–101. https://doi.org/10.1161/CIRCRESAHA.117.311312.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358(13):1336–45. https://doi.org/10.1056/NEJMoa072100.

    Article  CAS  PubMed  Google Scholar 

  33. Möhlenkamp S, Lehmann N, Moebus S, Schmermund A, Dragano N, Stang A, et al. Heinz Nixdorf Recall Study Investigators. Quantification of coronary atherosclerosis and inflammation to predict coronary events and all-cause mortality. J Am Coll Cardiol. 2011;57(13):1455–64. https://doi.org/10.1016/j.jacc.2010.10.043.

  34. Blaha MJ, Whelton SP, Al Rifai M, Dardari ZA, Shaw LJ, Al-Mallah MH, et al. Rationale and design of the coronary artery calcium consortium: a multicenter cohort study. J Cardiovasc Comput Tomogr. 2017;11:54–61. https://doi.org/10.1016/j.jcct.2016.11.004.

    Article  PubMed  Google Scholar 

  35. •• Wang FM, Rozanski A, Arnson Y, Budoff MJ, Miedema MD, Nasir K, et al. Cardiovascular and all-cause mortality risk by coronary artery calcium scores and percentiles among older adult males and females. Am J Med. 2021;134(3):341–50. https://doi.org/10.1016/j.amjmed.2020.07.024. Recent analysis of additive value in CAC for risk prediction.

    Article  CAS  PubMed  Google Scholar 

  36. Jee SH, Jang Y, Oh DJ, Oh BH, Lee SH, Park SW, et al. A coronary heart disease prediction model: the Korean Heart Study. BMJ Open. 2014;4(5): e005025. https://doi.org/10.1136/bmjopen-2014-005025.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Orimoloye OA, Banga S, Dardari ZA, Uddin SMI, Budoff MJ, Berman DS, et al. Coronary artery calcium as a predictor of coronary heart disease, cardiovascular disease, and all-cause mortality in Asian-Americans: The Coronary Artery Calcium Consortium. Coron Artery Dis. 2019;30(8):608–14. https://doi.org/10.1097/MCA.0000000000000746.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Chen J, Budoff MJ, Reilly MP, Yang W, Rosas SE, Rahman M, et al. Coronary artery calcification and risk of cardiovascular disease and death among patients with chronic kidney disease. JAMA Cardiol. 2017;2(6):635–43. https://doi.org/10.1001/jamacardio.2017.0363.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Xie Q, Ge X, Shang D, Li Y, Yan H, Tian J, et al. Coronary artery calcification score as a predictor of all-cause mortality and cardiovascular outcome in peritoneal dialysis patients. Perit Dial Int. 2016;36(2):163–70. https://doi.org/10.3747/pdi.2014.00124.

  40. Whelton SP, Al Rifai M, Dardari Z, Shaw LJ, Al-Mallah MH, Matsushita K, et al. Coronary artery calcium and the competing long-term risk of cardiovascular vs. cancer mortality: the CAC Consortium. Eur Heart J Cardiovasc Imaging. 2019;20(4):389–395. https://doi.org/10.1093/ehjci/jey176.

  41. Shaikh K, Li D, Nakanishi R, Kinninger A, Almeida S, Cherukuri L, et al. Low short-term and long-term cardiovascular and all-cause mortality in absence of coronary artery calcium: a 22-year follow-up observational study from large cohort. J Diabetes Complications. 2019;33(9):616–22. https://doi.org/10.1016/j.jdiacomp.2019.05.015.

    Article  PubMed  Google Scholar 

  42. Yamamoto H, Kitagawa T, Kunita E, Utsunomiya H, Senoo A, Nakamoto, et al. Impact of the coronary artery calcium score on mid- to long-term cardiovascular mortality and morbidity measured with coronary computed tomography angiography. Circ J. 2018;82(9):2342–2349. https://doi.org/10.1253/circj.CJ-18-0086.

  43. Dudum R, Dzaye O, Mirbolouk M, Dardari ZA, Orimoloye OA, Budoff MJ, et al. Coronary artery calcium scoring in low risk patients with family history of coronary heart disease: validation of the SCCT guideline approach in the coronary artery calcium consortium. J Cardiovasc Comput Tomogr. 2019;13(3):21–25. https://doi.org/10.1016/j.jcct.2019.03.012.

  44. •• Blaha MJ, Whelton SP, Al Rifai M, Dardari Z, Shaw LJ, Al-Mallah MH, et al. Comparing risk scores in the prediction of coronary and cardiovascular deaths: coronary artery calcium consortium. Cardiovascular Imaging. 2021;14(2):411–21. https://doi.org/10.1016/j.jcmg.2019.12.010. Direct comparison of three risk scores for coronary and CVD deaths.

    Article  PubMed  Google Scholar 

  45. Shaw LJ, Min JK, Nasir K, Xie JX, Berman DS, Miedema MD, et al. Sex differences in calcified plaque and long-term cardiovascular mortality: observations from the CAC Consortium. Eur Heart J. 2018;39(41):3727–35. https://doi.org/10.1093/eurheartj/ehy534.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Liew G, Chow C, van Pelt N, Younger J, Jelinek M, Chan J, et al. Cardiac Society of Australia and New Zealand position statement: coronary artery calcium scoring. Heart Lung Circ. 2017;26(12):1239–51. https://doi.org/10.1016/j.hlc.2017.05.130.

    Article  PubMed  Google Scholar 

  47. Savic L, Mrdovic I, Asanin M, Stankovic S, Krljanac G, Lasica R. Using the RISK-PCI score in the long-term prediction of major adverse cardiovascular events and mortality after primary percutaneous coronary intervention. J Interv Cardiol. 2019;24(2019):2679791. https://doi.org/10.1155/2019/2679791.

    Article  Google Scholar 

  48. Mrdovic I, Savic L, Krljanac G, Asanin M, Perunicic J, Lasica R, et al. Predicting 30-day major adverse cardiovascular events after primary percutaneous coronary intervention. The RISK-PCI score. Int J Cardiol. 2013;162(3):220–7. https://doi.org/10.1016/j.ijcard.2011.05.071.

  49. Fox KA, Dabbous OH, Goldberg RJ, Pieper KS, Eagle KA, Van de Werf F, et al. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE). BMJ. 2006;333(7578):1091. https://doi.org/10.1136/bmj.38985.646481.55.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Amsterdam EA, Wenger NK, Brindis RG, Casey DE, Ganiats TG, Holmes DR, et al. 2014 AHA/ACC guideline for the management of patients with non–ST-elevation acute coronary syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;64(24):e139-228. https://doi.org/10.1016/j.jacc.2014.09.017.

    Article  PubMed  Google Scholar 

  51. Collet JP, Thiele H, Barbato E, Barthélémy O, Bauersachs J, Bhatt DL, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the task force for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2021;42(14):1289–367. https://doi.org/10.1093/eurheartj/ehaa575.

    Article  PubMed  Google Scholar 

  52. Mehta SR, Granger CB, Boden WE, Steg PG, Bassand JP, Faxon DP, et al. Early versus delayed invasive intervention in acute coronary syndromes. N Engl J Med. 2009;360(21):2165–75. https://doi.org/10.1056/NEJMoa0807986.

    Article  CAS  PubMed  Google Scholar 

  53. Kofoed KF, Kelbæk H, Hansen PR, Torp-Pedersen C, Høfsten D, Kløvgaard L, et al. Early versus standard care invasive examination and treatment of patients with non-ST-segment elevation acute coronary syndrome: VERDICT randomized controlled trial. Circulation. 2018;138(24):2741–50. https://doi.org/10.1161/CIRCULATIONAHA.118.037152.

    Article  PubMed  Google Scholar 

  54. Huang W, FitzGerald G, Goldberg RJ, Gore J, McManus RH, Awad H, et al. Performance of the GRACE risk score 2.0 simplified algorithm for predicting 1-year death after hospitalization for an acute coronary syndrome in a contemporary multiracial cohort. Am J Cardiol. 2016;118(8):1105–10. https://doi.org/10.1016/j.amjcard.2016.07.029

  55. Fox KA, FitzGerald G, Puymirat E, Huang W, Carruthers K, Simon T, et al. Should patients with acute coronary disease be stratified for management according to their risk? Derivation, external validation and outcomes using the updated GRACE risk score. BMJ Open. 2014;4(2): e004425. https://doi.org/10.1136/bmjopen-2013-004425.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Antman EM, McCabe CH, Gurfinkel EP, Turpie AG, Bernink PJ, Salein D, et al. Enoxaparin prevents death and cardiac ischemic events in unstable angina/non-Q-wave myocardial infarction: results of the thrombolysis in myocardial infarction (TIMI) 11B trial. Circulation. 1999;100:1593–601. https://doi.org/10.1161/01.cir.100.15.1593.

    Article  CAS  PubMed  Google Scholar 

  57. Poldervaart JM, Langedijk M, Backus BE, Dekker IM, Six AJ, Doevendans PA, et al. Comparison of the GRACE, HEART and TIMI score to predict major adverse cardiac events in chest pain patients at the emergency department. Int J Cardiol. 2017;15(227):656–61. https://doi.org/10.1016/j.ijcard.2016.10.080.

    Article  Google Scholar 

  58. Heidenreich PA, Albert NM, Allen LA, Bluemke DA, Butler J, Fonarow GC, et al. American Heart Association Advocacy Coordinating Committee; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular Radiology and Intervention; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Stroke Council. Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circ Heart Fail. 2013;6(3):606–19. https://doi.org/10.1161/HHF.0b013e318291329a.

  59. Fonarow GC, Adams KF Jr, Abraham WT, Yancy CW, Boscardin WJ; ADHERE Scientific Advisory Committee, Study Group, and Investigators. Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. JAMA. 2005;293(5):572–80. https://doi.org/10.1001/jama.293.5.572.

  60. Peterson PN, Rumsfeld JS, Liang L, Albert NM, Hernandez AF, Peterson ED, et al. American Heart Association get with the guidelines-heart failure program. a validated risk score for in-hospital mortality in patients with heart failure from the American Heart Association get with the guidelines program. Circ Cardiovasc Qual Outcomes. 2010;3(1):25–32. https://doi.org/10.1161/CIRCOUTCOMES.109.854877.

  61. Pocock SJ, Wang D, Pfeffer MA, Yusuf S, McMurray JJ, Swedberg KB, et al. Predictors of mortality and morbidity in patients with chronic heart failure. Eur Heart J. 2006;27(1):65–75. https://doi.org/10.1093/eurheartj/ehi555.

    Article  PubMed  Google Scholar 

  62. Levy WC, Mozaffarian D, Linker DT, Sutradhar SC, Anker SD, Cropp AB, et al. The Seattle heart failure model. Circulation. 2006;113(11):1424–33. https://doi.org/10.1161/CIRCULATIONAHA.105.584102.

    Article  PubMed  Google Scholar 

  63. Lee DS, Austin PC, Rouleau JL, Liu PP, Naimark D, Tu JV. Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. JAMA. 2003;290:2581–7. https://doi.org/10.1001/jama.290.19.2581.

    Article  CAS  PubMed  Google Scholar 

  64. Rich JD, Burns J, Freed BH, Maurer MS, Burkhoff D, Shah SJ. Meta-analysis global group in chronic (MAGGIC) heart failure risk score: validation of a simple tool for the prediction of morbidity and mortality in heart failure with preserved ejection fraction. J Am Heart Assoc. 2018;7(20): e009594. https://doi.org/10.1161/JAHA.118.009594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Anjan VY, Loftus TM, Burke MA, Akhter N, Fonarow GC, Gheorghiade M, et al. Prevalence, clinical phenotype, and outcomes associated with normal B-type natriuretic peptide levels in heart failure with preserved ejection fraction. Am J Cardiol. 2012;110:870–6. https://doi.org/10.1016/j.amjcard.2012.05.014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Shah SJ. Innovative clinical trial designs for precision medicine in heart failure with preserved ejection fraction. J Cardiovasc Transl Res. 2017;10:322–36. https://doi.org/10.1007/s12265-017-9759-8.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Khan SS, Ning H, Shah SJ, Yancy CW, Carnethon M, Berry JD, et al. 10-year risk equations for incident heart failure in the general population. J Am Coll Cardiol. 2019;73(19):2388–97. https://doi.org/10.1016/j.jacc.2019.02.057.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Razavi AC, Potts KS, Kelly TN, He J, Fernandez C, Krousel-Wood M, et al. Pooled cohort equations heart failure risk score predicts cardiovascular disease and all-cause mortality in a nationally representative sample of US adults. BMC Cardiovasc Disord. 2020;20(1):202. https://doi.org/10.1186/s12872-020-01485-2.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Fuster V, Rydén LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, et al. Task Force on Practice Guidelines, American College of Cardiology/American Heart Association; Committee for Practice Guidelines, European Society of Cardiology; European Heart Rhythm Association; Heart Rhythm Society. ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation-executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines(Writing Committee to Revise the 2001 Guidelines for the Management of Patients with Atrial Fibrillation). Eur Heart J. 2006;27(16):1979–2030. https://doi.org/10.1093/eurheartj/ehl176.

  70. Vodošek Hojs N, Ekart R, Bevc S, Piko N, Hojs R. CHA2DS2-VASc score as a predictor of cardiovascular and all-cause mortality in chronic kidney disease patients. Am J Nephrol. 2021;11:1–8. https://doi.org/10.1159/000516121.

    Article  Google Scholar 

  71. Schamroth Pravda M, Cohen Hagai K, Topaz G, Schamroth Pravda N, Makhoul N, Shuvy M, et al. Assessment of the CHA2DS2-VASc score in predicting mortality and adverse cardiovascular outcomes of patients on hemodialysis. Am J Nephrol. 2020;51(8):635–40. https://doi.org/10.1159/000508836.

    Article  PubMed  Google Scholar 

  72. Nakagawa K, Hirai T, Takashima S, Fukuda N, Ohara K, Sasahara E, et al. Chronic kidney disease and CHADS(2) score independently predict cardiovascular events and mortality in patients with nonvalvular atrial fibrillation. Am J Cardiol. 2011;107(6):912–6. https://doi.org/10.1016/j.amjcard.2010.10.074.

    Article  PubMed  Google Scholar 

  73. Ruwald MH, Ruwald AC, Jons C, Lamberts M, Hansen ML, Vinther M, et al. Evaluation of the CHADS2 risk score on short- and long-term all-cause and cardiovascular mortality after syncope. Clin Cardiol. 2013;36(5):262–8. https://doi.org/10.1002/clc.22102.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Shuvy M, Klein E, Cohen T, Shlomo N, Rozenbaum Z, Pereg D. Value of adding the CHA2DS2-VASc score to the GRACE score for mortality risk prediction in patients with acute coronary syndrome. Am J Cardiol. 2019;123(11):1751–6. https://doi.org/10.1016/j.amjcard.2019.02.045.

    Article  PubMed  Google Scholar 

  75. Ivanovs R, Kivite A, Ziedonis D, Mintale I, Vrublevska J, Rancans E. Association of depression and anxiety with the 10-year risk of cardiovascular mortality in a primary care population of Latvia using the SCORE system. Front Psychiatry. 2018;26(9):276. https://doi.org/10.3389/fpsyt.2018.00276.

    Article  Google Scholar 

  76. O’Donnell M, Teo K, Gao P, Anderson C, Sleight P, Dans A, et al. Cognitive impairment and risk of cardiovascular events and mortality. Eur Heart J. 2012;33(14):1777–86. https://doi.org/10.1093/eurheartj/ehs053.

    Article  PubMed  Google Scholar 

  77. Kerola T, Hiltunen M, Kettunen R, Hartikainen S, Sulkava R, Vuolteenaho O, et al. Mini-mental state examination score and B-type natriuretic peptide as predictors of cardiovascular and total mortality in an elderly general population. Ann Med. 2011;43(8):650–9. https://doi.org/10.3109/07853890.2010.526137.

    Article  CAS  PubMed  Google Scholar 

  78. Minne L, Abu-Hanna A, de Jonge E. Evaluation of SOFA-based models for predicting mortality in the ICU: a systematic review. Crit Care. 2008;12(6):R161. https://doi.org/10.1186/cc7160.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Raith EP, Udy AA, Bailey M, McGloughlin S, MacIsaac C, Bellomo R, et al. Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcomes and Resource Evaluation (CORE). Prognostic Accuracy of the SOFA Score, SIRS Criteria, and qSOFA Score for In-Hospital Mortality Among Adults With Suspected Infection Admitted to the Intensive Care Unit. JAMA. 2017;317(3):290–300. https://doi.org/10.1001/jama.2016.20328.

  80. Aoyama D, Morishita T, Uzui H, Miyazaki S, Ishida K, Kaseno K, et al. Sequential organ failure assessment score on admission predicts long-term mortality in acute heart failure patients. ESC Heart Fail. 2020;7(1):244–52. https://doi.org/10.1002/ehf2.12563.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Jentzer JC, Bennett C, Wiley BM, Murphree DH, Keegan MT, Barsness GW. Predictive value of individual sequential organ failure assessment sub-scores for mortality in the cardiac intensive care unit. PLoS One. 2019;14(5): e0216177. https://doi.org/10.1371/journal.pone.0216177.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, May M, Brindle P. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ. 2007;335:136. https://doi.org/10.1136/bmj.39261.471806.55.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Woodward M, Brindle P, Tunstall-Pedoe H. for the SIGN Group on Risk Estimation. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish heart health extended cohort (SHHEC). Heart. 2007;93:172–176. https://doi.org/10.1136/hrt.2006.108167.

  84. Schulte H, Cullen P, Assmann G. Obesity, mortality and cardiovascular disease in the Münster Heart Study (PROCAM). Atherosclerosis. 1999;144(1):199–209. https://doi.org/10.1016/s0021-9150(99)00055-6.

    Article  CAS  PubMed  Google Scholar 

  85. Versteylen MO, Joosen IA, Shaw LJ, Narula J, Hofstra L. Comparison of Framingham, PROCAM, SCORE, and Diamond Forrester to predict coronary atherosclerosis and cardiovascular events. J Nucl Cardiol. 2011;18(5):904–11. https://doi.org/10.1007/s12350-011-9425-5.

    Article  PubMed  PubMed Central  Google Scholar 

  86. D'Agostino RB Sr, Grundy S, Sullivan LM, Wilson P. CHD Risk Prediction Group. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180–7. https://doi.org/10.1001/jama.286.2.180.

  87. Fernández-Torres R, Pita-Fernández S, Fonseca E. Psoriasis and cardiovascular risk. Assessment by different cardiovascular risk scores. J Eur Acad Dermatol Venereol. 2013;27(12):1566–70. https://doi.org/10.1111/j.1468-3083.2012.04618.x.

  88. Anderson JL, Ronnow BS, Horne BD, Carlquist JF, May HT, Bair TL, et al. Intermountain Heart Collaborative (IHC) Study Group. Usefulness of a complete blood count-derived risk score to predict incident mortality in patients with suspected cardiovascular disease. Am J Cardiol. 2007;99(2):169–74. https://doi.org/10.1016/j.amjcard.2006.08.015.

  89. Pocock SJ, McCormack V, Gueyffier F, Boutitie F, Fagard RH, Boissel JP. A score for predicting risk of death from cardiovascular disease in adults with raised blood pressure, based on individual patient data from randomised controlled trials. BMJ. 2001;323(7304):75–81. https://doi.org/10.1136/bmj.323.7304.75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Sotos-Prieto M, Mattei J, Cook NR, Hu FB, Willett WC, Chiuve SE, et al. Association between a 20-year cardiovascular disease risk score based on modifiable lifestyles and total and cause-specific mortality among US men and women. J Am Heart Assoc. 2018;7(21): e010052. https://doi.org/10.1161/JAHA.118.010052.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Wohlfahrt P, Bruthans J, Krajčoviechová A, Šulc P, Linhart A, Filipovský J, et al. Systematic coronary risk evaluation (SCORE) and 20-year risk of cardiovascular mortality and cancer. Eur J Intern Med. 2020;79:63–9. https://doi.org/10.1016/j.ejim.2020.05.034.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Cardiovascular Diseases, Department of Internal Medicine, Texas Tech University Health Sciences Center, El Paso, TX, USA

    Jose B. Cruz Rodriguez & Haider Alkhateeb

  2. Division of Cardiovascular Medicine, Department of Medicine, University of California San Diego, 9452 Medical Center Drive #7411, San Diego, CA, 92037, USA

    Jose B. Cruz Rodriguez

  3. Department of Internal Medicine, Dell Seton Medical Center, at The University of Texas, Austin, TX, USA

    Khan O. Mohammad

Authors
  1. Jose B. Cruz Rodriguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Khan O. Mohammad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haider Alkhateeb
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jose B. Cruz Rodriguez.

Ethics declarations

Conflict of Interest

The authors declare no competing interests.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Ischemic Heart Disease

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cruz Rodriguez, J.B., Mohammad, K.O. & Alkhateeb, H. Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths. Curr Cardiol Rep 24, 7–15 (2022). https://doi.org/10.1007/s11886-021-01620-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11886-021-01620-1

Keywords

Search

Navigation