Prediction of atrial fibrillation in patients with coronary artery disease using mathematical modeling methods
https://doi.org/10.15829/1560-4071-2025-5868
EDN: KTACGP
Abstract
Aim. To create a method for assessing the probability of atrial fibrillation (AF) in patients with coronary artery disease (CAD).
Material and methods. Our openlabel, continuous, retrospective, nonrandomized study included data from female and male patients (n=181) with a diagnosis of CAD who were treated at the City Clinical Hospital № 1 (cardiology department) in Novosibirsk for CAD from September 2022 to September 2023. Based on the data obtained, models for predicting the probability of AF detection were developed.
Results. Prognostic models of AF risk in patients with CAD were constructed. The model with explanatory variables (left ventricular ejection fraction, hypertension, highdensity lipoprotein level, GG variant of the interleukin6 gene) showed a sensitivity of 84% and a specificity of 92% in a leaveoneout cross validation.
Conclusion. The constructed prognostic method for assessing the risk of AF in patients with CAD has good prognostic value and is quite easy to use, including for practical healthcare physicians.
About the Authors
S. V. Kuzin
Federal Research Center for Fundamental and Translational Medicine
Russian Federation
Russian Federation
Novosibirsk
N. G. Lozhkina
Federal Research Center for Fundamental and Translational Medicine
Russian Federation
Russian Federation
Novosibirsk
E. I. Shefer
Sobolev Institute of Mathematics
Russian Federation
Russian Federation
Novosibirsk
P. S. R.
Sobolev Institute of Mathematics
Russian Federation
Russian Federation
Novosibirsk
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For citations:
Kuzin S.V., Lozhkina N.G., Shefer E.I., R. P.S. Prediction of atrial fibrillation in patients with coronary artery disease using mathematical modeling methods. Russian Journal of Cardiology. 2025;30(5):5868. (In Russ.) https://doi.org/10.15829/1560-4071-2025-5868. EDN: KTACGP
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