Comparison of Framingham Risk Score (FRS) and QRISK2 Result for Adult in Productive Age to WHO Chart
DOI:
https://doi.org/10.53366/jimki.v8i3.135Keywords:
CVD, Framingham Risk Score, QRISK2Abstract
Background:Framingham Risk Score and QRISK2 are cardiovascular desease (CVD) risk prediction recommended by American Heart Association for early detection of CVD to reduce morbidity and mortality. The primary purpose of this research is to compare the result from FRS and QRISK2 for adult in productive age in Jakarta.
Method:This research is conducted using a cross-sectional diagnostic test. We collected primary data from 173 respondents in Wijaya Kusuma, Grogol, Jakarta Barat from September 2018 to November 2018. The data collected are medical history and results from blood pressure, cholesterol, and BMI. All the data entry is calculated by FRS and QRISK2 online calculator, then further analyzed by SPSS program.
Results:ROC value for FRS and QRISK2 are 0.60 and 0.69. The sensitivity, spesifity, positive predicting value, and negative predicting value for FRS are 31%, 90%, 35%, and 88%. In another hand, QRISK2 are 58%,81%, 34%, and 91%. This analysis shows that QRISK2 have a higher accuracy compared to FRS.
Conclusion:This research shows that there is a difference between FRS and QRISK2 in CVD risk calculation. QRISK2 have higher sensitivity and specifity compared to FRS, but FRS have a better positive and negative predicting value compared to QRISK2. From this research we concluded that use FRS to predict CVD risk in primary care is better compared to QRISK2.
References
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5. D’Agostino RB, Pencina MJ, Massaro JM, Coady S. Cardiovascular Disease Risk Assessment: Insights from Framingham. Global Heart 2013;8(1):11-23. doi:10.1016/j.gheart.2013.01.001. Accessed April 12, 2018
6. Genest J, McPherson R, Frohlich J, Anderson T, Campbell N, Carpentier A, et al. 2009 Canadian Cardiovascular Society/Canadian guidelines for the diagnosis and treatment of dyslipid- emia and prevention of cardiovascular disease in the adult: 2009 recommendations. Can J Cardiol 2009;25:567–569. Accessed April 12, 2018
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8. Chia Yook Chin, Gray Sarah YW, Ching Aiew M, Lim Hooi Min, Chinna Karuthan. Validation of The Framingham General Cardiovascular Risk Score in Multiethnic Asian Population: a Retrospective Cohort Study. BMJ Open 2015;5:e007324. Accessed April 14, 2018
9. Selvarajah Sharmini, Kaur Gurpreet, Haniff Jamaiyah, Cheong Kee Chee, Hiong Tee Guat, Bots Mivhiel L, et al. Comparison of The Framingham Risk Score, SCORE, and WHO/ISH Cardiovascular Risk Prediction Models in an Asian Population. International Journal of Cardiology 2014;176(1):211-18. Accessed April 15, 2018
10. Tillin Therese, Hudges Alun D, Whincup Peter, Mayet Jamil, Sattar Naveed, McKeigue Paul M, et al. Ethnicity and Prediction of Cardiovascular Disease: Performance of QRISK2 and Framingham Scores in UK Tri-ethnic Prospective Cohort Study. Heart 2014;100:60-7. Accessed April 21, 2018
11. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Seikh Aziz, Brindle P. Predicting Cardiovascular Risk in England and Wales: Prospective Derivation and Validation of QRISK2. BMJ 2008;336:1475-82. Accessed April 21, 2018
12. Sohn C, Kim J, Bae W. The Framingham Risk Score, Diet, and Inflamatory Merkers in Korean Men with Metabolic Syndrome. Nutr Res Pract 2012;6(3):246–253. doi: 10.4162/nrp.2012.6.3.246. Accessed April 14, 2018
13. Van Staa Tjeerd Pieter, Gulliford Martin, Ng Edmond S W, Goldacre Ben, Smeeth Liam. Prediction of Cardiovascular Risk Using Framingham, ASSIGN, and QRISK2: How Well DO They Predict Individual Rather than Population Risk?. PLoS ONE 2014;9(10): e106455. Accessed April 20, 2018
14. Garg Naveen, Muduli Subrat K, Kapoor Aditya, Tewari Satyendra, Kumar Sudeep, Khanna Roopali, et al. Comparison of Differerent Cardiovascular Risk Score Calculators for Cardiovascular Risk Prediction and Guidline Recommended Statin Uses. Indian Heart Journal 2017;69:458-63. Accessed Mei 1, 2018
15. Ofori Sandra N, Odia Osaretin J. Risk Assessment in The Prevention of Cardivascular Disease in Low-resource Settings. Indian Heart Jurnal 2016;68(3):391-98. Accesssed April 17, 2018
16. World Health Organization. WHO/ISH Risk Prediction Charts. Available at sh-world.com/downloads/.../colour_charts_24_Aug_07.pdf. Accessed June 4, 2018
17. Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, et al. American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2010;122:e584–e636. Accessed April 12, 2018
18. Pike Mindy M, Decker Paul A, Larson Nicholas B, Sauver Jenniver L, Takahashi Paul Y, Roger Veronique L, et al. Improvement in Cardiovascular Risk Prediction with Electronic Health Records. J Cardiovas Transl Res 2016;9(3):214-22. Accessed Mei 1, 2018
2. Global Atlas on Cardiovascular Disease Prevention and Control. Mendis S, Puska P, Norrving B editors World Health Organization in Collaboration with the World Heart Federation and World Stroke Organization, Geneve 2011:2-7
3. Riset Kesehatan Dasar 2013. Available at www.depkes.go.id/resources/download/general/Hasil%20Riskesdas%202013.pdf. Accessed April 12, 2018
4. Pusat Data dan Informasi Kementrian Kesehatan RI. Available at www.depkes.go.id/download.php?file.../pusdatin/infodatin/infodatin-jantung.pdf. Accessed April 12, 2018
5. D’Agostino RB, Pencina MJ, Massaro JM, Coady S. Cardiovascular Disease Risk Assessment: Insights from Framingham. Global Heart 2013;8(1):11-23. doi:10.1016/j.gheart.2013.01.001. Accessed April 12, 2018
6. Genest J, McPherson R, Frohlich J, Anderson T, Campbell N, Carpentier A, et al. 2009 Canadian Cardiovascular Society/Canadian guidelines for the diagnosis and treatment of dyslipid- emia and prevention of cardiovascular disease in the adult: 2009 recommendations. Can J Cardiol 2009;25:567–569. Accessed April 12, 2018
7. Khalili Davood, Hadaegh Farzad, Soori Hamid, Steyerberg Ewout W, Bazorgmanesh Mohammadreza, Azizi Fereidoun. Clinical Usefulness of The Framingham Cardiovascular Risk Profile Beyond Its Statistical Performance. American Journal of Epidemiology 2012;176(3):177–186. Accessed April 14, 2018
8. Chia Yook Chin, Gray Sarah YW, Ching Aiew M, Lim Hooi Min, Chinna Karuthan. Validation of The Framingham General Cardiovascular Risk Score in Multiethnic Asian Population: a Retrospective Cohort Study. BMJ Open 2015;5:e007324. Accessed April 14, 2018
9. Selvarajah Sharmini, Kaur Gurpreet, Haniff Jamaiyah, Cheong Kee Chee, Hiong Tee Guat, Bots Mivhiel L, et al. Comparison of The Framingham Risk Score, SCORE, and WHO/ISH Cardiovascular Risk Prediction Models in an Asian Population. International Journal of Cardiology 2014;176(1):211-18. Accessed April 15, 2018
10. Tillin Therese, Hudges Alun D, Whincup Peter, Mayet Jamil, Sattar Naveed, McKeigue Paul M, et al. Ethnicity and Prediction of Cardiovascular Disease: Performance of QRISK2 and Framingham Scores in UK Tri-ethnic Prospective Cohort Study. Heart 2014;100:60-7. Accessed April 21, 2018
11. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Seikh Aziz, Brindle P. Predicting Cardiovascular Risk in England and Wales: Prospective Derivation and Validation of QRISK2. BMJ 2008;336:1475-82. Accessed April 21, 2018
12. Sohn C, Kim J, Bae W. The Framingham Risk Score, Diet, and Inflamatory Merkers in Korean Men with Metabolic Syndrome. Nutr Res Pract 2012;6(3):246–253. doi: 10.4162/nrp.2012.6.3.246. Accessed April 14, 2018
13. Van Staa Tjeerd Pieter, Gulliford Martin, Ng Edmond S W, Goldacre Ben, Smeeth Liam. Prediction of Cardiovascular Risk Using Framingham, ASSIGN, and QRISK2: How Well DO They Predict Individual Rather than Population Risk?. PLoS ONE 2014;9(10): e106455. Accessed April 20, 2018
14. Garg Naveen, Muduli Subrat K, Kapoor Aditya, Tewari Satyendra, Kumar Sudeep, Khanna Roopali, et al. Comparison of Differerent Cardiovascular Risk Score Calculators for Cardiovascular Risk Prediction and Guidline Recommended Statin Uses. Indian Heart Journal 2017;69:458-63. Accessed Mei 1, 2018
15. Ofori Sandra N, Odia Osaretin J. Risk Assessment in The Prevention of Cardivascular Disease in Low-resource Settings. Indian Heart Jurnal 2016;68(3):391-98. Accesssed April 17, 2018
16. World Health Organization. WHO/ISH Risk Prediction Charts. Available at sh-world.com/downloads/.../colour_charts_24_Aug_07.pdf. Accessed June 4, 2018
17. Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, et al. American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2010;122:e584–e636. Accessed April 12, 2018
18. Pike Mindy M, Decker Paul A, Larson Nicholas B, Sauver Jenniver L, Takahashi Paul Y, Roger Veronique L, et al. Improvement in Cardiovascular Risk Prediction with Electronic Health Records. J Cardiovas Transl Res 2016;9(3):214-22. Accessed Mei 1, 2018
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Published
2021-02-23
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Research Article
How to Cite
Comparison of Framingham Risk Score (FRS) and QRISK2 Result for Adult in Productive Age to WHO Chart. (2021). JIMKI: Jurnal Ilmiah Mahasiswa Kedokteran Indonesia, 8(3), 41-46. https://doi.org/10.53366/jimki.v8i3.135
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