Agreement between cardiovascular disease risk assessment tools: An application to the United Arab Emirates population

Autoři: Abderrahim Oulhaj aff001;  Sherif Bakir aff003;  Faisal Aziz aff004;  Abubaker Suliman aff001;  Wael Almahmeed aff006;  Harald Sourij aff002;  Abdulla Shehab aff007
Působiště autorů: Institute of Public Health, College of Medicine & Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates aff001;  Zayed Center for Health Sciences, United Arab Emirates University, United Arab Emirates aff002;  Cardiology Department, Sheikh Shakhbout Medical City, United Arab Emirates aff003;  Cardiovascular Diabetology Research Group, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria aff004;  Center for Biomarker Research in Medicine (CBmed), Graz, Austria aff005;  Heart and Vascular Institute, Cleveland Clinic, Abu Dhabi, United Arab Emirates aff006;  Department of Internal Medicine, College of Medicine & Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates aff007
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article



Evidence regarding the performance of cardiovascular disease (CVD) risk assessment tools is limited in the United Arab Emirates (UAE). Therefore, we assessed the agreement between various externally validated CVD risk assessment tools in the UAE.


A secondary analysis of the Abu Dhabi Screening Program for Cardiovascular Risk Markers (AD-SALAMA) data, a large population-based cross-sectional survey conducted in Abu Dhabi, UAE during the period 2009 until 2015, was performed in July 2019. The analysis included 2,621 participants without type 2 Diabetes and without history of cardiovascular diseases. The CVD risk assessment tools included in the analysis were the World Health Organization for Middle East and North Africa Region (WHO-MENA), the systematic coronary risk evaluation for high risk countries (SCORE-H), the pooled cohort risk equations for white (PCRE-W) and African Americans (PCRE-AA), the national cholesterol education program Framingham risk score (FRAM-ATP), and the laboratory Framingham risk score (FRAM-LAB).


The overall concordance coefficient was 0.50. The agreement between SCORE-H and PCRE-W, PCRE-AA, FRAM-LAB, FRAM-ATP and WHO-MENA, were 0.47, 0.39, 0.0.25, 0.42 and 0.18, respectively. PCRE-AA classified the highest proportion of participants into high-risk category of CVD (16.4%), followed by PCRE-W (13.6%), FRAM-LAB (6.9%), SCORE-H (4.5%), FRAM-ATP (2.7%), and WHO-MENA (0.4%).


We found a poor agreement between various externally validated CVD risk assessment tools when applied to a large data collected in the UAE. This poses a challenge to choose any of these tools for clinical decision-making regarding the primary prevention of CVD in the country.

Klíčová slova:

Africa – Cardiovascular diseases – Coronary heart disease – diabetes mellitus – Global health – Hypertension – Cholesterol – Medical risk factors


1. World Health Organization. WHO | Cardiovascular diseases (CVDs). [Cited 2019 Jan 03]. Available from: Published 2017.

2. World Health Organization. United Arab Emirates: World Health Organization—Noncommunicable Diseases (NCD) Country Profiles, 2018. [Cited 2019 July 21]. Available from: Published 2018.

3. Radaideh G, Tzemos N, Ali TM, Eldershaby Y, Joury J, Abreu P. Cardiovascular Risk Factor Burden in the United Arab Emirates (UAE): The Africa Middle East (AfME) Cardiovascular Epidemiological (ACE) Study Sub-analysis. Int Cardiovasc Forum J. 2017;11(0). Available from:

4. Lloyd-Jones DM. Cardiovascular Risk Prediction. Circulation. 2010;121(15): 1768–1777. doi: 10.1161/CIRCULATIONAHA.109.849166 20404268

5. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart J. 2003;24(11): 987–1003.

6. Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D' Agostino RB, Gibbons R, et al. 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk. Circulation. 2014;129(25): S49–S73.

7. National Cholesterol Education Program (NCEP). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation. 2002;106(25): 3143–3143. 12485966

8. D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6): 743–753. doi: 10.1161/CIRCULATIONAHA.107.699579 18212285

9. World Health Organization, International Society of Hypertension. WHO/ISH Risk prediction charts for 14 WHO epidemiological sub-regions. World Health Organization/International Society of Hypertension;2007. [Cited 2019 Jan 30]. Available from: Published 2007.

10. World Health Organization. Prevention of cardiovascular disease. Pocket Guidelines for Assessment and Management of Cardiovascular Risk. [Cited 2019 Jan 30]. Available from: Published 2007.

11. Al-Rawahi A, Lee P. Applicability of the Existing CVD Risk Assessment Tools to Type II Diabetics in Oman: A Review. Oman Med J. 2015;30(5): 315–319. doi: 10.5001/omj.2015.65 26421110

12. Steichen TJ, Cox NJ. A note on the concordance correlation coefficient. Stata J. 2002;2(2): 183–189.

13. Barnhart HX, Haber M, Song J. Overall concordance correlation coefficient for evaluating agreement among multiple observers. Biometrics. 2002;58(4): 1020–1027. doi: 10.1111/j.0006-341x.2002.01020.x 12495158

14. McBride G. A proposal for strength-of-agreement criteria for Lins Concordance Correlation Coefficient [Internet]. 2005 [Cited 2019 Jan 30]. Report No.: HAM2005-062. Available from:

15. Damen JA, Hooft L, Schuit E, Debray TPA, Collins GS, Tzoulaki I, et al. Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ. 2016;353: i2416. doi: 10.1136/bmj.i2416 27184143

16. Bazo-Alvarez JC, Quispe R, Peralta F, Poterico JA, Valle GA, Burroughs M, et al. Agreement Between Cardiovascular Disease Risk Scores in Resource-Limited Settings: Evidence from 5 Peruvian Sites. Crit Pathw Cardiol. 2015;14(2): 74–80. doi: 10.1097/HPC.0000000000000045 26102017

17. Allan GM, Nouri F, Korownyk C, Kolber MR, Vandermeer B, McCormack J. Agreement among cardiovascular disease risk calculators. Circulation. 2013;127(19): 1948–1956. doi: 10.1161/CIRCULATIONAHA.112.000412 23575355

18. Bansal M, Kasliwal RR, Trehan N. Relationship between different cardiovascular risk scores and measures of subclinical atherosclerosis in an Indian population. Indian Heart J. 2015;67(4): 332–3340. doi: 10.1016/j.ihj.2015.04.017 26304565

19. Motamed N, Rabiee B, Perumal D, Poustchi H, Miresmail SJ, Farahani B, et al. Comparison of cardiovascular risk assessment tools and their guidelines in evaluation of 10-year CVD risk and preventive recommendations: A population based study. Int J Cardiol. 2017;228: 52–57. doi: 10.1016/j.ijcard.2016.11.048 27863362

20. Garg N, Muduli SK, Kapoor A, Tewari S, Kumar S, Khanna R, et al. Comparison of different cardiovascular risk score calculators for cardiovascular risk prediction and guideline recommended statin uses. Indian Heart J. 2017;69(4): 458–463. doi: 10.1016/j.ihj.2017.01.015 28822511

21. 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): 211–218. doi: 10.1016/j.ijcard.2014.07.066 25070380

22. DeFilippis AP, Young R, Carrubba CJ, McEvoy JW, Budoff MJ, Blumenthal RS, et al. An analysis of calibration and discrimination among multiple cardiovascular risk scores in a modern multiethnic cohort. Ann Intern Med. 2015;162(4): 266–275. doi: 10.7326/M14-1281 25686167

23. Allan GM, Garrison S, McCormack J. Comparison of cardiovascular disease risk calculators. Curr Opin Lipidol. 2014;25(4): 254–265. doi: 10.1097/MOL.0000000000000095 24977979

24. Muntner P, Colantonio LD, Cushman M, Goff DC, Howard G, Howard VJ, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014;311(14): 1406–1415. doi: 10.1001/jama.2014.2630 24682252

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2020 Číslo 1
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