Best Risk Score in Predicting Hard Cardiovascular Events in Patients with First Myocardial Infarction
Background:Although a number of risk assessment models are available for estimating 10-year risk of cardiovascular (CV) events in patients requiring primary prevention of CV disease, the predictive accuracy of the contemporary risk models has not been adequately evaluated in Indians.
Methods: 412 patients [mean age 55.7±12.8 years; 320 (77.7%) males] without prior CV disease and presenting with acute myocardial infarction (MI) were included. The six clinically relevant risk assessment models [Framingham Risk score (RiskFRS-L), Framingham Risk score (RiskFRS-B), World Health Organization risk prediction charts (RiskWHO), American College of Cardiology/ American Heart Association pooled cohort equations (RiskACC/AHA) and the 3rd Joint British Societies' risk calculator (RiskJBS), Predicting cardiovascular risk in England and Wales(RiskQRISK2)]. Risk scores were applied to estimate what would have been their predicted 10-year risk of CV events if they had presented just prior to suffering the acute MI.
Results: RiskACC/AHA provided the lowest risk estimates with 74.4% patients estimated to be having <20% 10-year risk. RiskJBS provided intermediate risk (67.3% with risk, 20%). In comparison, RiskFRS-L and RiskFRS-B, Risk returned higher risk estimates (53.6% and 50.1% with risk <20%, respectively; p values <0.001 for comparison with RiskWHO). However, RiskQRISK-2 identified the highest proportion of the patients as being at high-risk the (only 51% at <20% risk, p values 0 < 0.01 for comparison with RiskACC/AHA, RiskJBS risk scores).
Conclusion: This is the first study to show that in Indian patients presenting with acute MI, RiskQRISK-2 is likely to identify the largest proportion of the patients as at high-riskas compared to RiskWHO, RiskFRS-L, RiskFRS-B and RiskACC/AHA. However, large-scale prospective studies are needed to confirm these findings.
2. D'Agostino Sr RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the framingham heart study. Circulation. 2008; 117: 743- 753.
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 munster (procam) study. Circulation. 2002; 105: 310- 315.
4. Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten- year risk of fatal cardiovascular disease in Europe: the score project. Eur Heart J. 2003; 24: 987-1003.
5. Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of qrisk2. BMJ. 2008; 336: 1475- 1482.
6. 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.
7. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Brindle P. Performance of the qrisk cardiovascular risk prediction algorithm in an independent uk sample of patients from general practice: a validation study. Heart. 2008;94: 34- 39.
8. World health organization. Prevention of Cardiovascular Disease Guidelines for Assessment and Management of Cardiovascular Risk. Geneva: WHO; 2007.
9. Goff Jr DC, Lloyd-Jones DM, Bennett G, 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. Circulation. 2014; 129 (25 Suppl 2): S49-S73.
10. Joint British Societies' consensus recommendations for the prevention of cardiovascular disease (jbs3). Heart. 2014; 100 (suppl 2): ii1- ii67.
11. Anand SS, Yusuf S, Vuksan V, et al. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic Groups (share). Lancet. 2000; 356: 279- 284.
12. McKeigue PM, Miller GJ, Marmot MG. Coronary heart disease in south Asians overseas: a review. J Clin Epidemiol. 1989; 42: 597-609.
13. Joshi P, Islam S, Pais P, et al. Risk factors for early myocardial infarction in south Asians compared with individuals in other countries. JAMA. 2007; 297: 286- 294.
14. Perumal L, Wells S, Ameratunga S, et al. Markedly different clustering of cvd risk factors in New Zealand Indian and European people but similar risk scores (predict-14). Aust N Z J Public Health. 2012; 36: 141- 144.
15. Bhopal R, Fischbacher C, Vartiainen E, Unwin N, White M, Alberti G. Predicted and observed cardiovascular disease in south Asians: application of finrisk, framingham and score models to Newcastle Heart Project data. J Public Health (Oxford, England). 2005; 27: 93- 100.
16. Liem SS, Oemrawsingh PV, Cannegieter SC, et al. Cardiovascular risk in young apparently healthy descendents from Asian Indian migrants in the Netherlands: the shiva study. Neth Heart J. 2009; 17: 155- 161.
17. Enas EA, Garg A, Davidson MA, Nair VM, Huet BA, Yusuf S. Coronary heart disease and its risk factors in first-generation immigrant Asian Indians to the United States Of America. Indian Heart J. 1996; 48: 343- 353.
18. Thygesen K, Alpert JS, Jaffe AS, et al. Third universal definition of myocardial infarction. Eur Heart J. 2012; 33: 2551- 2567.
19. O'Gara PT, Kushner FG, Ascheim DD, et al. 2013 ACCF/ AHA guideline for the management of st-elevation myocardial infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2013; 61: e78- 140.
20. Jneid H, Anderson JL, Wright RS, et al. 2012 ACCF/AHA focused update of the guideline for the management of patients with unstable angina/non-st-elevation myocardial infarction (updating the 2007 guideline and replacing the 2011 focused update): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2012; 60: 645- 681.
21. Chia YC. Review of tools of cardiovascular disease risk stratification: interpretation, customisation and application in clinical practice. Singapore Med J. 2011; 52: 116- 123.
22. Bansal M, Shrivastava S, Mehrotra R, Agarwal V, Kasliwal RR. Low framingham risk score despite high prevalence of metabolic syndrome in asymptomatic North-Indian population. J Assoc Physicians India. 2009; 57: 17-22.
23. Kanjilal S, Rao VS, Mukherjee M, et al. Application of cardiovascular disease risk prediction models and the relevance of novel biomarkers to risk stratification in Asian Indians. Vasc Health Risk Manag. 2008; 4: 199- 211.
24. Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force On Practice Guidelines. Circulation. 2014; 129 (25 Suppl 2): S1-S45.
25. Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet. 2013; 382: 1762- 1765.
26. Amin NP, Martin SS, Blaha MJ, Nasir K, Blumenthal RS, Michos ED. Headed in the right direction but at risk for miscalculation: a critical appraisal of the 2013 ACC/AHA risk assessment guidelines. J Am Coll Cardiol. 2014; 63 (25PA): 2789- 2794.
27. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2, BMJ 2008; 336: 1475-82.
28. Enas EA, Singh V, Munjal YP, et al. Recommendations of the second Indo-U.S. health summit on prevention and control of cardiovascular disease among Asian Indians. Indian Heart J. 2009; 61: 265- 274.
29. Akosah KO, Schaper A, Cogbill C, Schoenfeld P. Preventing myocardial infarction in the young adult in the first place: how do the national cholesterol education panel iii guidelines perform? J Am Coll Cardiol. 2003; 41: 1475-1479.
Copyright (c) 2021 Amit Chaudhary , Akanksha Verma
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.