FRAMINGHAM RISK SCORE SEBAGAI ALAT DETEKSI DINI PENYAKIT JANTUNG PADA KELOMPOK BERISIKO : SISTEMATIK LITERATUR REVIEW
DOI:
https://doi.org/10.31004/jkt.v6i1.40793Keywords:
Cardiovascular Disease, Framingham Risk Score, Populasi BerisikoAbstract
Cardiovascular Disease (CVD) merupakan masalah global dan penyakit utama yang dapat menghilangkan nyawa di dunia. Salah satu upaya menurunkan angka mortalitas dan morbiditas CVD adalah kemampuan untuk mengenali penyakit ini lebih cepat. Framingham Risk Score (FRS) merupakan alat atau model yang dapat diadaptasi secara klinis untuk mendeteksi penyakit jantung. Tujuan dari penelitian ini adalah mengetahui efektivitas FRS sebagai alat deteksi dini penyakit jantung pada kelompok berisiko. Metode penelitian ini adalah sistematik review yang menggunakan database elektronik untuk mencari artikel. Pencarian menggunakan 3 keyword “Framingham Risk Score”, “Cardiovascular Disease”, “Risk Population”. Inklusi artikel penelitian ini adalah artikel menjelaskan tentang efektivitas FRS untuk memprediksi penyakit jantung pada kelompok beresiko dalam waktu 10 tahun, publikasi artikel 2014-2024, ditulis dengan Bahasa inggris, dan full text. Artikel akan tereksklusi jika artikel merupakan letters to editor, commentary, isi artikel hanya menjelaskan distribusi frekuensi. Pada proses pencarian didapatkan 166.253 artikel dari 3 database. Setelah dikombinasikan menggunakan dengan AND terdapat 2 artikel pada PUBMED, 97 artikel pada Science Direct dan 122 artikel pada Google Scholar. Artikel yang memenuhi kriteria inklusi dan eksklusi terdapat 8 artikel, 0 artikel dari PUBMED, 3 Science Direct, dan 5 dari Google Scholar. Setelah dilakukan analisa didapatkan hasil dari 5 artikel menyatakan bahwa FRS lebih unggul dibandingkan dengan model yang lain. FRS juga memiliki sensitivitas dan kalibrasi yang baik dalam memprediksi risiko penyakit jantung. FRS terbukti efektif untuk digunakan sebagai alat yang digunakan untuk memprediksi risiko penyakit jantung pada kelompok berisiko.References
AHA. (2015). Coronary Artery Disease-Coronary Heart Disease. https://www.heart.org/en/health-topics/consumer-healthcare/what-is-cardiovascular-disease/coronary-artery-disease
AHA. (2018). Heart Disease and Stroke Statistics 2018 At-a-Glance. https://www.heart.org/-/media/data-import/downloadables/heart-disease-and-stroke-statistics-2018---at-a-glance-ucm_498848.pdf
Al-Shamsi, S. (2020). Performance of the Framingham coronary heart disease risk score for predicting 10-year cardiac risk in adult United Arab Emirates nationals without diabetes: a retrospective cohort study. BMC Family Practice, 21(1), 175. https://doi.org/10.1186/s12875-020-01246-2
Arnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., Himmelfarb, C. D., Khera, A., Lloyd-Jones, D., McEvoy, J. W., Michos, E. D., Miedema, M. D., Muñoz, D., Smith, S. C., Virani, S. S., Williams, K. A., Yeboah, J., & Ziaeian, B. (2019). 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation, 140(11), e596–e646. https://doi.org/10.1161/CIR.0000000000000678
Artigao-Rodenas, L. M., Carbayo-Herencia, J. A., Divisón-Garrote, J. A., Gil-Guillén, V. F., Massó-Orozco, J., Simarro-Rueda, M., Molina-Escribano, F., Sanchis, C., Carrión-Valero, L., López de Coca, E., Caldevilla, D., López-Abril, J., Carratalá-Munuera, C., Lopez-Pineda, A., & (GEVA)¶, on behalf of the G. de E. V. de A. (2013). Framingham Risk Score for Prediction of Cardiovascular Diseases: A Population-Based Study from Southern Europe. PLOS ONE, 8(9), e73529-. https://doi.org/10.1371/journal.pone.0073529
Bhatnagar, P., Wickramasinghe, K., Wilkins, E., & Townsend, N. (2016). Trends in the epidemiology of cardiovascular disease in the UK. Heart, 102(24), 1945–1952. https://doi.org/10.1136/heartjnl-2016-309573
Borhanuddin, B., Mohd Nawi, A., Shah, S. A., Abdullah, N., Syed Zakaria, S. Z., Kamaruddin, M. A., Velu, C. S., Ismail, N., Abdullah, M. S., & Ahmad Kamat, S. (2018). 10‐Year cardiovascular disease risk estimation based on lipid profile‐based and BMI‐based framingham risk scores across multiple sociodemographic characteristics: the Malaysian cohort project. The Scientific World Journal, 2018(1), 2979206.
Damen, J. A., Pajouheshnia, R., Heus, P., Moons, K. G. M., Reitsma, J. B., Scholten, R. J. P. M., Hooft, L., & Debray, T. P. A. (2019). Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis. BMC Medicine, 17(1), 109. https://doi.org/10.1186/s12916-019-1340-7
FHS (Framingham Heart Study). (2018). Hard Coronary Heart Disease (10-year risk). https://www.framinghamheartstudy.org/fhs-risk-functions/hard-coronary-heart-disease-10-year-risk/
Flueckiger, P., Longstreth, W., Herrington, D., & Yeboah, J. (2018). Revised Framingham Stroke Risk Score, Nontraditional Risk Markers, and Incident Stroke in a Multiethnic Cohort. Stroke, 49(2), 363–369. https://doi.org/10.1161/STROKEAHA.117.018928
Günaydın, Z. Y., Karagöz, A., Bektaş, O., Kaya, A., Kırış, T., Erdoğan, G., Işık, T., & Ayhan, E. (2016). Comparison of the Framingham risk and SCORE models in predicting the presence and severity of coronary artery disease considering SYNTAX score. Anatol J Cardiol, 16, 412–418. https://doi.org/10.5152/AnatolJCardiol.2015.6317
Gupta, R., Mohan, I., & Narula, J. (2016). Trends in Coronary Heart Disease Epidemiology in India. Annals of Global Health, 82(2), 307–315. https://doi.org/10.1016/j.aogh.2016.04.002
Jian, J. Z., Tzeng, I. S., Hsieh, C. F., Huang, H. L., Chen, C. L., & Liu, K. L. (2023). Validation of the Framingham General Cardiovascular Risk Score and Pooled Cohort Equations in a Community-Based Population: A Prospective Cohort Study Analysis 2006-2017. Acta Cardiologica Sinica, 39(6), 879–887. https://doi.org/10.6515/ACS.202311_39(6).20230405A
Jinn, J. (2014). Testing for “silent” Coronary Heart Disease. JAMA : The Journal of The American Medical Association, 32(8), 858.
Kasim, S. S., Ibrahim, N., Malek, S., Ibrahim, K. S., Aziz, M. F., Song, C., Chia, Y. C., Ramli, A. S., Negishi, K., & Mat Nasir, N. (2023). Validation of the general Framingham Risk Score (FRS), SCORE2, revised PCE and WHO CVD risk scores in an Asian population. The Lancet Regional Health – Western Pacific, 35. https://doi.org/10.1016/j.lanwpc.2023.100742
Kemenkes. (2017). Penyakit Jantung Penyebab Kematian Tertinggi, Kemenkes Ingatkan CERDIK.
Luengo-Fernandez, R., Leal, J., & Gray, A. (2015). UK research spend in 2008 and 2012: Comparing stroke, cancer, coronary heart disease and dementia. BMJ Open, 5(4), 1–8. https://doi.org/10.1136/bmjopen-2014-006648
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., Group, P., & Grp, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ: British Medical Journal. https://doi.org/10.1136/bmj.b2535
Petruzzo, M., Reia, A., Maniscalco, G. T., Luiso, F., Lanzillo, R., Russo, C. V., Carotenuto, A., Allegorico, L., Palladino, R., Brescia Morra, V., & Moccia, M. (2021). The Framingham cardiovascular risk score and 5-year progression of multiple sclerosis. European Journal of Neurology, 28(3), 893–900. https://doi.org/https://doi.org/10.1111/ene.14608
Riskesdas. (2018). Riset Kesehatan Dasar. www.depkes.go.id/resources/download/.../hasil-riskesdas-2018.pdf
Roth, G. A., Huffman, M. D., Moran, A. E., Feigin, V., Mensah, G. A., Naghavi, M., & Murray, C. J. L. (2015). Global and regional patterns in cardiovascular mortality from 1990 to 2013. Circulation, 132(17), 1667–1678. https://doi.org/10.1161/CIRCULATIONAHA.114.008720
Sayin, Cetiner, M., Karabag, T., Akpinar, I., Sayin, EKurcer, M., Dogan, S., & Aydin, M. (2014). Framingham risk score and severity of coronary artery disease. Herz, 39(5), 638–543. https://doi.org/10.1007/s00059-013-3881-4
Selvarajah, S., Kaur, G., Haniff, J., Cheong, K. C., Hiong, T. G., van der Graaf, Y., & Bots, M. L. (2014). Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. International Journal of Cardiology, 176(1), 211–218. https://doi.org/https://doi.org/10.1016/j.ijcard.2014.07.066
Tousoulis, D. (2017). Coronary Artery Disease: From Biology to Clinical Practice. Elsevier Inc.
WHO. (2018). Indonesia: statistical profile. WHO - Noncomunicable Disease Country Profiles. http://www.who.int/gho/countries/idn.pdf?ua=1
Yang, W., Ma, R., Zhang, X., Guo, H., He, J., Mao, L., Mu, L., Hu, Y., Yan, Y., Liu, J., Ma, J., Li, S., Ding, Y., Zhang, M., Zhang, J., & Guo, S. (2018). Comparison Between Metabolic Syndrome and the Framingham Risk Score as Predictors of Cardiovascular Diseases Among Kazakhs in Xinjiang. Scientific Reports, 8(1), 16474. https://doi.org/10.1038/s41598-018-34587-1
Downloads
Published
Issue
Section
License
Copyright (c) 2025 ANGERNANI TRIAS Wulandari, Abdul Qodir, Dwi Soelistyoningsih

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).