Cardiovascular risk stratification in stable coronary artery disease based on prognostic scores and models
https://doi.org/10.15829/1728-8800-2020-2528
Abstract
According to modern clinical guidelines, the strategy of examination and treatment of a patient with stable coronary artery disease depends on the prognosis. Despite the great number of prognostic models and scores, there is currently no unified approach for cardiovascular risk stratification. The article provides a literature review of the main current prognostic models and scores, taking into account their effectiveness and limitations.
About the Authors
S. N. TolpyginaRussian Federation
Moscow
S Yu. Martsevich
Russian Federation
Moscow
References
1. Тask Force Members, Montalescot G, Sechtem U, et al. 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J. 2013;34(38):2949-3003. doi:10.1093/eurheartj/eht296.
2. Mark DB, Nelson CL, Califf RM, et al. Continuing evolution of therapy for coronary artery disease: initial results from the era of coronary angioplasty. Circulation. 1994;89:2015-25. doi:10.1161/01.cir.89.5.2015.
3. Emond M, Mock MB, Davis KB, et al. Long-term survival of medically treated patients in the Coronary Artery Surgery Study (CASS) Registry. Circulation. 1994;(90)6:2645-57. doi:10.1161/01.cir.90.6.2645.
4. Califf RM, Phillips HR, Hindman MC, et al. Prognostic value of a coronary artery jeopardy score. J Am Coll Cardiol. 1985;5:1055- 63. doi:10.1016/s0735-1097(85)80005-x.
5. Califf RM, Armstrong PW, Carver JR, et al. 27th Bethesda Conference: matching the intensity of risk factor management with the hazard for coronary disease events. Task Force 5. Stratification of patients into high, medium and low risk subgroups for purposes of risk factor management. J Am Coll Cardiol. 1996;5(27):1007-19. doi:10.1016/0735-1097(96)87733-3.
6. Sianos G, Morel MA, Kappetein AP, et al. The SYNTAX Score: an angiographic tool grading the complexity of coronary artery disease. EuroIntervention. 2005;(1)2:219-27.
7. Farooq V, Vergouwe Y, Raber L, et al. Combined anatomical and clinical factors for the long-term risk stratification of patients undergoing percutaneous coronary intervention: the Logistic Clinical SYNTAX score. Eur Heart J. 2012;(33)24:3098-104. doi:10.1093/eurheartj/ehs295.
8. Farooq V, van Klaveren D, Steyerberg EW, et al. Anatomical and clinical characteristics to guide decision making between coronary artery bypass surgery and percutaneous coronary intervention for individual patients: development and validation of SYNTAX score II. Lancet. 2013;(381)9867:639-50. doi:10.1016/s0140-6736(13)60108-7.
9. Clayton TC, Lubsen J, Pocock SJ, et al. Risk score for predicting death, myocardial infarction, and stroke in patients with stable angina, based on a large randomised trial cohort of patients. BMJ. 2005;(331)7521:869. doi:10.1136/bmj.38603.656076.63.
10. Mark DB, Shaw L Jr, Harrell FE, et al. Prognostic value of a treadmill exercise score in outpatients with suspected coronary artery disease. N Engl J Med. 1991;(325)12:849-53. doi:10.1056/nejm199109193251204.
11. Koltunov IE, Mazayev VP, Martsevich SYu. A comprehensive evaluation of the results of exercise stress on the treadmill to stratify patients into risk groups. Cardiovascular Therapy and Prevention. 2003;3:53-8. (In Russ.)
12. Martsevich SYu, Tolpygina SN, Malysheva AM, et al. Role of selected parameters and integral indices of treadmill test in the assessment of complication risk among patients with chronic coronary heart disease. Cardiovascular Therapy and Prevention. 2012;11(2):44-52. (In Russ.) doi:10.15829/1728-8800-2012-2-44-52.
13. Lipinski M, Froelicher V, Atwood E, et al. Comparison of treadmill scores with physician estimates of diagnosis and prognosis in patients with coronary artery disease. Am Heart J. 2002;(143)4:650-8. doi:10.1067/mhj.2002.120967.
14. Fearon WF, Gauri J, Myers J, et al. A comparison of treadmill scores to diagnose coronary artery disease. Clin Cardiol. 2002;(25)3:117- 22. doi:10.1002/clc.4960250307.
15. Lauer MS, Pothier CE, Magid DJ, et al. An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram. Ann Intern Med. 2007;(147)12:821-8. doi:10.7326/0003-4819-147-12-200712180-00001.
16. Daly CA, De Stavola B, Sendon JL, et al. Predicting prognosis in stable angina-results from the Euro heart survey of stable angina: prospective observational study. BMJ. 2006;(332)7536:262-7. doi:10.1136/bmj.38695.605440.ae.
17. Daly C, Norrieb J, Murdochc DL, et al. The value of routine non-invasive tests to predict clinical outcome in stable angina. Eur Heart J. 2003;(24)6:532-40. doi:10.1016/s0195-668x(02)00820-5.
18. Elhendy A, Schinkel FL, van Domburg RT, et al. Risk stratification of patients with angina pectoris by stress 99mTc-tetrofosmin myocardial perfusion imaging. J Nucl Med. 2005;(46)12:2003-8.
19. IONA Study Group. Determinants of coronary events in patients with stable angina: results from the impact of nicorandil in angina study. Am Heart J. 2005;(150)4:689. doi:10.1016/j.ahj.2005.03.040.
20. Hemingway H, McCallum A, Shipley M, et al. Incidence and prognostic implications of stable angina pectoris among women and men. JAMA. 2006;(295)12:1404-11. doi:10.1001/jama.295.12.1404.
21. Pozdniakov NV, Tatarchenko IP, Soloviev KV. Instrumental assessment of risk factors in the prediction of cardiac events in ischemic heart disease. Functional diagnostics. 2010;3:19-22. (In Russ.)
22. Komarov AL, Ilyushchenko TA, Shakhmatova OO, et al.Comparative Efficacy of Conservative and Invasive Treatment of Patients With Stable Form of Ischemic Heart Disease (According to Results of Five Year Prospective Study). Kardiologiia. 2012;52(8):4-14. (In Russ.)
23. Tolpygina SN, Martsevich SY, Gofman EA, Deev AD. Novel Scale for Long-Term Prognostication of Risk of Death and Nonfatal Cardiovascular Complications in Patients From the PROGNOSISIHD Registry. Kardiologiia. 2016;6(56):12-7. (In Russ.) doi:10.18565/cardio.2016.6.12-17.
24. Sachdev M, Sun JL, Tsiatis AA, et al. The prognostic importance of comorbidity for mortality in patients with stable coronary artery disease. J Am Coll Cardiol. 2004;(43)4:576-82. doi:10.1016/j.jacc.2003.10.031.
25. Charlson ME, Pompei P, Ales HL. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;(40)5:373-83. doi:10.1016/0021-9681(87)90171-8.
26. Wilson PWF, D’Agostino R Sr, Bhatt DL, et al. An international model to predict recurrent cardiovascular disease. Am J Med. 2012;125(7):695-703. doi:10.1016/j.amjmed.2012.01.014.
27. Rapsomaniki E, Shah A, Perel P, et al. Prognostic models for stable coronary artery disease based on electronic health record cohort of 102023 patients. Eur Heart J. 2014;35(13):844-52. doi:10.1093/eurheartj/eht533.
28. Pocock S, Bueno H, Licour M, et al. Predictors of one-year mortality at hospital discharge after acute coronary syndromes: A new risk score from the EPICOR (long-tErm follow uP of antithrombotic management patterns In acute CORonary syndrome patients) study. Eur Heart J: Acute Cardiovasc Care. 2015;(4)6:509-17. doi:10.1177/2048872614554198.
Review
For citations:
Tolpygina S.N., Martsevich S.Yu. Cardiovascular risk stratification in stable coronary artery disease based on prognostic scores and models. Cardiovascular Therapy and Prevention. 2020;19(3):2528. (In Russ.) https://doi.org/10.15829/1728-8800-2020-2528