A Multiple Logistic Regression Model as an Additional Mathematical Method for Predicting the Development of Ischemic Stroke in Patients with Atrial Fibrillation
International Journal of Biomedicine. 2018;8(4):284-287.
Originally published December 15, 2018
Prevention of thromboembolic complications in cases of atrial fibrillation (AF) and, above all, ischemic stroke (IS), represents a key problem of modern cardiology. The aim of the present study was to assess the feasibility of Multiple Logistic Regression Analysis in predicting the occurrence of IS in AF patients with the predictor genotypes of the FGB, GPIα, and GPIβα genes, in order to implement an approach to primary prevention and personalized treatment.
Methods and Results: We examined 43 patients with atrial fibrillation and IS in their histories and 78 patients with AF without IS. A total of 188 persons without AF were included in the control group. The present study showed that the homozygote minor allele genotype (AA) of the FGB -455G/A SNP, the minor allele CT and TT genotypes of the GPIa 807C/T SNP, and the -5C/-5C and -5C/-5T genotypes of the GPIβα −5T/C polymorphism can be studied as genetic predictors of IS in AF patients. Logistic regression analysis was used to predict the development of IS in AF patients, depending on the presence of pathological genotypes of the FGB, GPIα, and GPIβα genes. The percentage of correct predictions for the absence of IS using this model was 99.5%. The development of IS was correctly predicted in 7.0% of cases. The overall percentage of correct predictions was 82.3%.
Conclusion: The obtained logistic regression model is recommended as an additional method for assessing the risk of IS in young patients with isolated AF.
- Morozova TE, Andrushchishina TB. [Thromboembolic complications prevention in patients with atrial fibrillation]. Farmateka. 2014;9:81–87. [Article in Russian].
- Napalkov DA, Sokolova AA. [A rational approach to the choice of anticoagulant therapy for the prevention of strokes in patients with nonvalvular atrial fibrillation]. Sechenovsky Bulletin. 2014;1:55–62. [Article in Russian].
- Novikova NA, Keiko OI. [Ischemic stroke prevention in patients with nonvalvular atrial fibrillation: the role of dabigatran etexilate]. Doctor.Ru. 2014.4: 38–41. [Article in Russian].
- Panchenko EP, Dobrovolsky AB. [Thromboses in cardiology. Mechanisms of development and treatment options]. Moscow: Sport i Kultura, 1999: 217–243. [Article in Russian].
- Zotova IV, Isaeva MIu, Vanieva OS,Tsymbalova ТЕ, Alekhin MN. Zateishchikov DA. [The system of hemostasis in patients with atrial fibrillation: markers of left auricular thrombosis]. Kardiologiia. 2008;48(2):36–40. [Article in Russian]. PubMed
- Sumarokov AV, Mikhailov AA. Cardiac arrythmias. Мoscow: Meditsina; 1986. [In Russian].
- Sychov DA, Kropacheva ES, Ignat'ev IV, Bulytova IuM, Dobrovol'skiĭ AB, Panchenko EP, Kukes VG. [Pharmacogenetics of indirect anticoagulants: value of genotype for improvement of efficacy and safety of therapy]. Kardiologiia. 2006;46(7):72-7.[Article in Russian]. PubMed
- Stewart S, Hart CL, Hole DJ, McMurray JJ. A population-based study of the long-term risks associated with atrial fibrillation: 20-year follow-up of the Renfrew/Paisley study. Am J Med. 2002;113(5):359-64. PubMed
- Diagnosis and treatment of atrial fibrillation. Recommendation of RCS, ASSC and ACS. Rus J Cardiol. 2013; 4(3):100. [Article in Russian].
- Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al.; ESC Scientific Document Group. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 2016 Oct 7;37(38):2893-2962. doi: 10.1093/eurheartj/ehw210. PubMed
- Serdechnaya EV. Atrial fibrillation: peculiarities of clinical course and choice of treatment strategy. Abstract of ScD Thesis. Moscow; 2008. [In Russian].
- Serdyuk I.Yu. Polymorphism of antithrombin genes in patients with ischemic stroke. Abstract of ScD Thesis. Moscow; 2008. [In Russian].
- Guilyarov M.Yu. Thromboembolic complications in patients with atrial fibrillation: factors influencing the risk of their development and antithrombotic therapy effectiveness. Abstract of ScD Thesis. Moscow; 2011. [In Russian].
- Shulman VA, Aksyutina NV, Nikulina SYu, Nazarov BV, Dudkina KV, Maksimov VN, Kozlov VV, Kotlovsky MYu, Sinyapko SF, Platunova IM. [Genetic predictors of cardioembolic stroke in patients with atrial fibrillation]. Rus J Cardiol. 2014;10:29-33. [Article in Russian].
- Pollard J.H. A Handbook of Numerical and Statistical Techniques: With Examples Mainly from the Life Sciences. Cambridge University Press;1979.
- Frank MB, Reiner AP, Schwartz SM, Kumar PN, Pearce RM, Arbogast PG, et al. The Kozak sequence polymorphism of platelet glycoprotein Ibalpha and risk of nonfatal myocardial infarction and nonfatal stroke in young women. Blood. 2001 Feb 15;97(4):875-9. PubMed
- Zeng Y, Zhang L, Hu Z, Yang Q, Ma M, Liu B, et al. 807C/T polymorphism of platelet glycoprotein Ia gene is associated with cerebral hemorrhage in a Chinese population. Int J Neurosci. 2016;126(8):729-33. doi: 10.3109/00207454.2015.1067891. PubMed
- Hu X, Wang J, Li Y, Wu J, Qiao S, Xu S, et al. The β-fibrinogen gene 455G/A polymorphism associated with cardioembolic stroke in atrial fibrillation with low CHA2DS2-VaSc score. Sci Rep. 2017;7(1):17517. doi: 10.1038/s41598-017-17537-1. PubMed
- Aksyutina NV, Shulman VA, Nikulina SYu, Nazarov BV, Maksimov VN, Plita EV, Kotlovsky MYu, Vereshchagina TD. [Clinical-Genetic riskometer for the ischemic stroke risk assessment in atrial fibrillation]. Rus J Cardiol. 2015;10: 42- 45. [Article in Russian].
Received October 26, 2018.
Accepted November 12, 2018.
©2018 International Medical Research and Development Corporation.