Comparability of cardiovascular risk assessment according to the SCORE and the coronary artery calcium score (Agatston score)

Aim. To determine whether the Systematic Coronary Risk Evaluation (SCORE) level corresponds to the coronary artery calcium (CAC) score (Agatston score).

Material and methods. The study included 212 people aged 40-65 years (mean age, 56,5±7,9 years). The number of men and women was 54 (25,5%) and 158 (74,5%), respectively.

Results. According to the SCORE, the groups were distributed as follows: 62 (29,2%) — low risk, 128 (60,4%) — moderate risk, 16 (7,5%) — high risk, 6 (2,8%) — very high risk. The average SCORE level for the general group was 2,5±2,4%. According to the Agatston score, the groups were distributed as follows: minimal risk (0-10) — 142 (67%) people, low risk (11-100) — 42 (19,8%) people, moderate risk (101-400) — 17 (8%) people, high risk (≥401) — 7 (3,3%) people. Inconsistencies for all categories of cardiovascular risk were revealed between SCORE and Agatston score.

Conclusion. The identified inconsistencies in the distribution of risk groups in accordance with the SCORE and Agatston score indicate that the SCORE scale is insufficiently informative. Multislice computed tomography coronary angiography with CAC calculation is additionally recommended, which will allow determining patient management and deciding on therapy. A comparative analysis of CAC score and the SCORE scale can help optimize, first of all, drug therapy for patients with hypertension and lipid metabolism disorders.

1. Roth GA, Mensah GA, Johnson CO, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: update from the GBD 2019 study. J Am Coll Cardiol. 2020;76:2982-3021.

2. Tsao CW, Aday AW, Almarzooq ZI, et al. Heart disease and stroke statistics — 2022 update: a report from the American Heart Association. Circulation. 2022;145:e153-e639.

3. Yusuf S, Hawken S, Ounpuu S, et al. INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364:937-52.

4. Prevention of chronic noncommunicable diseases in the Russian Federation. National Guideline 2022. Cardiovascular Therapy and Prevention. 2022;21(4):3235. (In Russ.) doi:10.15829/1728-88002022-335.

5. Urazalina SJ. Stratification of cardiovascular risk, current status of the problem. Russian medical J. 2012;18;(5):39-45. (In Russ.) doi:10.17816/rmj38091.

6. Solovey SP. Problems of stratification of cardiovascular risk and its reduction in primary prevention. Medical News. 2018;(6):4-11. (In Russ.)

7. Rodgers A, Ezzati M, Vander Hoorn S, et al. Distribution of Major Health Risks: Findings from the Global Burden of Disease Study. PLoS Med. 2004;1(1):e27. doi:10.1371/journal.pmed.0010027.

8. Marques-Vidal P, Rodondi N, Bochud M, et al. Predictive accuracy and usefulness of calibration of the ESC SCORE in Switzerland. Eur J Cardiovasc Prev Rehabil. 2008;(4):402-8. doi:10.1097/HJR.0b013e3282fb040f.

9. Tasneem ZN, Ming-Sum L. Carotid intima-media thickness and plaque in cardiovascular risk assessment. ACC Cardiovasc Imaging. 2014;7(10):1025-38. doi:10.1016/j.jcmg. 2013.11.014.

10. Van der Bijl N, Joemai RM, Geleijns J, et al. Assessment of Agatston coronary artery calcium score using contrast-enhanced CT coronary angiography. AJR. Am Journal of roentgenology. 2010;63;195(6):1299-305. doi:10.2214/AJR.09.3734.

11. Dweck MR, Khaw JH, Sng GK, et al. Aortic stenosis, atherosclerosis, and skeletal bone: is there a common link with calcification and inflammation? Eur Heart J. 2013;34(21):1567-74. doi:10.1093/eurheartj/eht034.

12. Katamadze NO, Berstein LL, Grishkin Yu N. Subclinical atherosclerosis imaging as a component of a comprehensive strategy for cardiovascular risk stratification. Cardiovascular Therapy and Prevention. 2012;11(2):76-84. (In Russ.)

13. Sandfort V, Bluemke DA. CT calcium scoring. History, current status and outlook. Diagn Interv Imaging. 2017;98(1):3-10. doi: 10.1016/j.diii.2016.06.007.

14. Rumberger JA, Brundage BH, Rader DJ, et al. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc. 1999;74:243-52. doi:10.4065/74.3.243.

15. Erbel R, Mohlenkamp S, Moebus S, et al. Coronary risk stratification, discrimination, and reclassification improvement based on quantification of subclinical coronary atherosclerosis. Heinz Nixdorf recall study. J Am Coll Cardiol. 2010;56:1397-406. doi:10.1016/j.jacc.2010.06.030.

16. Greenland P, Blaha MJ, Budoff MJ, et al. Coronary Calcium Score and Cardiovascular Risk. J Am Coll Cardiol. 2018;72(4):434-47. doi:10.1016/j.jacc.2018.05.027.

17. Nikolaev AE, Shapiev AN, Blokhin IA, et al. New approaches for assessing coronary changes in multi-layer spiral computed tomography. Russian Journal of Cardiology. 2019;(12):124-30. (In Russ.) doi:10.15829/1560-4071-2019-12-124-130.

18. Arad Y, Spadaro LA, Goodman K, et al. Prediction of coronary events with electron beam computed tomography. J Am Coll Cardiol. 2000;36(4):1253-60. doi:10.1016/s0735-1097(00)00872-x.

19. Thelen M, Erbel R, Kreitner K-F, Barkhausen J. Cardiac Imaging. A Multimodality Approach. Thieme. (2009) Print ISBN 9783131477811. Online ISBN 9783131493316. Book. doi:10. 1055/b-002-79366.

20. Elias-Smale SE, Proença RV, Koller MT, et al. Coronary calcium score improves classification of coronary heart disease risk in the elderly: the Rotterdam study. J Am Coll Cardiol. 2010;56:1407-14. doi:10.1016/j.jacc.2010.06.029.

21. Johnson K, David A Dowe D. The detection of any coronary calcium outperforms Framingham risk score as a first step in screening for coronary atherosclerosis. AJR Am J Roentgenol. 2010;194(5):1235-43. doi:10.2214/AJR.09.2487.