The Probability of Stroke Based on Clinical Decision Support System (CDSS) using the Framingham Risk Score Method in Hospital

  • Arinda Lironika Suryana Politeknik Negeri Jember
  • Mudafiq Riyan Pratama Politeknik Negeri Jember
  • Gamasiano Alfiansyah Politeknik Negeri Jember
Keywords: CDSS, Framingham Risk Score, Hospital, Medical Record, Stroke

Abstract

Stroke is the main cause of death in Indonesia. Identification of stroke risk factors can use the Clinical Decision Support System (CDSS). Researchers have designed and developed a CDSS using the Framingham Risk Score (FRS) method to identify stroke in patients. The study aims to identify stroke risk factors using CDSS with the Framingham Risk Score method in dr Soebandi Hospital.This research was an analytic observational study using secondary data from medical record documents of neurology patients. . The sampling technique used was incidental sampling that met the inclusion criteria and exclusion criteria. The inclusion criteria used in selecting medical records were medical records that had complete data regarding gender, age, systolic blood pressure, total cholesterol, HDL, smoking behavior, history of diabetes mellitus, and the patient's stroke incidence thus obtaining 14 patient medical records.. Data were analyzed using the FRS method. Based on the research results, it can be concluded that there were 8 patients with high risk and 6 patients with low risk. However, further research needs to be carried out on the relationship between variables so that they can contribute in more detail to efforts to reduce the prevalence of stroke in society.

Downloads

Download data is not yet available.

References

Venketasubramanian N, Yudiarto FL, Tugasworo D. Stroke Burden and Stroke Services in Indonesia. Cerebrovasc Dis Extra. 2022;12(1):53–7.

Kusuma Y, Venketasubramanian N, Kiemas LS, Misbach J. Burden of stroke in Indonesia. Int J Stroke. 2009;4(October):379–80.

Putri AAN. Epidemiological Overview of Stroke in East Java 2019-2021. Prepotif J Kesehat Masy. 2023;7(1):1030–7.

Azzahra V, Ronoatmodjo S. Factors Associated with Stroke in Population Aged >15 Years in Special Region of Yogyakarta (Analysis of Basic Health Research 2018). J Epidemiol Kesehat Indones. 2023;6(2):91–6.

Ikhtiar I, Rosyich MW, Ardhanu MA, Bastiana DS, Kurniawan D, Setyowatie S. Stroke Risk Factor Profile in an Urban Population: A Community-Based Descriptive Study in Mojo Sub-District, Surabaya, Indonesia. Aksona. 2023;3(1):1–6.

Alharbi AS, Alhayan MS, Alnami SK, Traad RS, Aldawsari MA, Alharbi SA, et al. Epidemiology and Risk Factors of Stroke. Arch Pharm Pract. 2019;10(4):60–6.

Boehme AK, Esenwa C, Elkind MSV. Stroke Risk Factors, Genetics, and Prevention. Circ Res. 2017;120(3):472–95.

Ciplak S, Adiguzel A, Deniz YZ, Aba M, Ozturk U. The Role of the Low-Density Lipoprotein/High-Density Lipoprotein Cholesterol Ratio as an Atherogenic Risk Factor in Young Adults with Ischemic Stroke: A Case—Control Study. Brain Sci. 2023;13(8):1–9.

Zhang X xue, Wei M, Shang L xiang, Lu Y mei, Zhang L, Li Y dong. LDL-C / HDL-C is associated with ischaemic stroke in patients with non-valvular atrial fibrillation : a case-control study. Lipids Health Dis. 2020;19:1–11.

Qiao Z, Zhang F, Lu H, Xu Y, Zhang G. Research on the Medical Knowledge Deduction Based on the Semantic Relevance of Electronic Medical Record. Int J Comput Intell Syst. 2023;16(1):1–12.

Ackermann K, Baker J, Green M, Fullick M, Varinli H. Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients : Scoping Review. J Med Internet Res. 2022;24(2):1–23.

Baig MM, Hosseini HG, Lindén M. Machine learning-based clinical decision support system for early diagnosis from real-time physiological data. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON. 2017. p. 2943–6.

Ray JM, Ahmed OM, Solad Y, Maleska M, Martel S, Jeffery MM, et al. Computerized Clinical Decision Support System for Emergency Department – Initiated Buprenorphine for Opioid Use Disorder : User-Centered Design. JMIR Hum Factors. 2019;6(1):1–13.

Zikos D, Delellis N. CDSS-RM: A clinical decision support system reference model. BMC Med Res Methodol. 2018;18(1):1–14.

Sheikhtaheri A, Orooji A, Pazouki A, Beitollahi M. A Clinical Decision Support System for Predicting the Early Complications of One-Anastomosis Gastric Bypass Surgery. Obes Surg. 2019;29(7):2276–86.

Middleton B, Sittig DF, Wright A. Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision. Yearb Med Inform. 2016 Aug 6;25(S 01):S103–16.

Erawantini F, Suryana AL, Karimah RN, Jinan N, Afandi K, Wibowo NS, et al. Design Clinical Decision Support System (CDSS) in Electronic Health Record to Early Detection of Stroke Disease , Diabetes Mellitus and to Prevent Interaction of Drug Content. In: The 2nd International Conference on Social Science, Humanity and Public Health (ICOSHIP 2021). 2022. p. 307–10.

Bos D, Ikram MA, Leening MJG, Ikram MK. The revised Framingham stroke risk profile in a primary prevention population: The Rotterdam study. Circulation. 2017;135(22):2207–9.

Junaidi A, Marisdina S, Masita, Indrajaya T, Bahar E. Correlation between Framingham risk score and degree of asymptomatic intracranial artery stenosis on stroke prone person. In: Sriwijaya International Conference on Medical and Sciences. 2019. p. 1–5.

Sui Y, Chen Y, Lian J, Wang W. Predicting acute ischemic stroke using the revised Framingham stroke risk profile and multimodal magnetic resonance imaging. Front Neurol. 2023;14(September):1–9.

Appelros P, Stegmayr B, Terent A. Sex differences in stroke epidemiology: A systematic review. Stroke. 2009;40(4):1082–90.

Bushnell CD, Johnston DCC, Goldstein LB. Retrospective assessment of initial stroke severity comparison of the NIH stroke scale and the Canadian Neurological Scale. Stroke. 2001;32(3):656–60.

Watila M., Nyandaiti Y., Bwala S., Ibrahim A. Gender variation in risk factors and clinical presentation of acute stroke, Northeastern Nigeria. J Neurosci Behav Heal. 2011;3(3):38–43.

Thomas Q, Crespy V, Duloquin G, Ndiaye M, Sauvant M, Béjot Y, et al. Stroke in women: When gender matters. Rev Neurol (Paris). 2021;177(8):881–9.

Kelly-Hayes M. Influence of Age and Health Behaviors on Stroke Risk: Lessons from Longitudinal Studies. J Am Geriatr Soc. 2010;58(Suppl 2):1–8.

Suiraoka IP. Degenerative Diseases: Recognizing, Preventing And Reducing Risk Factors For 9 Degenerative Diseases. Yogyakarta: Nuha Medika; 2012.

Ekker MS, Boot EM, Singhal AB, Tan KS, Debette S, Tuladhar AM, et al. Epidemiology, aetiology, and management of ischaemic stroke in young adults. Lancet Neurol. 2018;17(9):790–801.

Guzik A, Bushnell C. Stroke Epidemiology and Risk Factor Management. Contin Lifelong Learn Neurol. 2017;23(1):15–39.

Oesch L, Tatlisumak T, Arnold M, Sarikaya H. Obesity paradox in stroke - Myth or reality? A systematic review. PLoS One. 2017;12(3):1–13.

Hackam DG, Hegele RA. Cholesterol Lowering and Prevention of Stroke: An Overview. Stroke. 2019;50(2):537–41.

Negara CK, Erna, Anna. The Effect of Cucumber Juice (Cucumis Sativus) Toward Hypertension of Elderly at Tresna Werdha Budi Sejahtera Social Institution of Banjarbaru South Borneo 2017. Indones J Nurs Pract. 2018;2(1):16–21.

Sarini, Suharyo. Several risk factors associated with stroke (case study at Dr. Kariadi Central General Hospital, Semarang). J Kesehat Masy Nas. 2008;3(2):153–64.

Listiana D, Isgiyanto A, Saputra MA. The Relationship between Total Cholesterol Level with Incidence of Stroke on Patient Who Treated at dr. M. Yunus Hospital Bengkulu. J Sains Kesehat. 2018;25(1):65–74.

Kim MK, Han K, Kim HS, Park YM, Kwon HS, Yoon KH, et al. Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: A nationwide population-based study. Eur Heart J. 2017;38(48):3560–6.

Yi SW, Shin DH, Kim H, Yi JJ, Ohrr H. Total cholesterol and stroke mortality in middle-aged and elderly adults: A prospective cohort study. Atherosclerosis. 2018;270:211–7.

Peters SAE, Carcel C, Millett ERC, Woodward M. Sex differences in the association between major risk factors and the risk of stroke in the UK Biobank cohort study. Neurology. 2020;95(20):E2715–26.

Wang HK, Huang CY, Sun YT, Li JY, Chen CH, Sun Y, et al. Smoking Paradox in Stroke Survivors?: Uncovering the Truth by Interpreting 2 Sets of Data. Stroke. 2020;51(4):1248–56.

Huangfu X, Zhu Z, Zhong C, Bu X, Zhou Y, Tian Y, et al. Smoking, Hypertension, and Their Combined Effect on Ischemic Stroke Incidence: A Prospective Study among Inner Mongolians in China. J Stroke Cerebrovasc Dis. 2017;26(12):2749–54.

Wajngarten M, Silva GS. Hypertension and Stroke: Update on Treatment. Eur Cardiol Rev. 2019;14(2):111–5.

Irwanadi MC. Hypertension Primary. Jakarta: Internal Publishing; 2014.

Saputra M, Negara CK, Martiana A, Puspasari H, Murjani A. Correlation Of Blood Cholesterol Levels And Hypertension With The Incidence Of Stroke In The Provincial Hospital Of Banjarmasin. INJEC. 2019;4(1):55–60.

Sethi R, Hiremath JS, Ganesh V, Banerjee S, Shah M, Mehta A, et al. Correlation between Stroke Risk and Systolic Blood Pressure in Patients over 50 Years with Uncontrolled Hypertension: Results from the SYSTUP-India Study. Cardiovasc Ther. 2021;2021:1–7.

Sofiana L, Rahmawati DD. Hypertension and Diabetes Mellitus Increase the Risk of Stroke. KEMAS J Kesehat Masy. 2019;15(2):147–52.

Willmot M, Leonardi-Bee J, Bath PMW. High Blood Pressure in Acute Stroke and Subsequent Outcome A Systematic Review. Hypertension. 2004;43(1):18–24.

Daneshfard B, Izadi S, Shariat A, Toudaji MA, Beyzavi Z, Niknam L. Epidemiology of stroke in Shiraz, Iran. Iran J Neurol. 2015;14(3):158–63.

Feigin V. Stroke: An Illustrated Guide to Stroke Prevention and Recovery. Jakarta: Bhuana Ilmu Populer; 2006.

Chen R, Ovbiagele B, Feng W. Diabetes and Stroke: Epidemiology, Pathophysiology, Pharmaceuticals and Outcomes. Am J Med Sci. 2016;351(4):380–386.

Tugasworo D, Retnaningsih. Stroke A-Z. Semarang: UNDIP Press; 2018.

Published
2024-01-05
How to Cite
Suryana, A. L., Pratama, M. R., & Alfiansyah, G. (2024). The Probability of Stroke Based on Clinical Decision Support System (CDSS) using the Framingham Risk Score Method in Hospital. ARTERI : Jurnal Ilmu Kesehatan, 5(1), 9-17. https://doi.org/10.37148/arteri.v5i1.412
Section
Articles