Changes in oscillatory and nonlinear dynamic processes of microcirculation in patients with obliterating atherosclerosis of lower limb arteries after revascularization
https://doi.org/10.29001/2073-8552-2023-38-1-75-81
Abstract
Aim: To study the nature of changes in oscillatory and nonlinear dynamic processes in the skin microcirculatory system by laser Doppler flowmetry in patients with obliterating atherosclerosis of the lower limbs arteries (OALLA) after limb revascularization.
Material and Methods. 27 male patients with OALLA before and after endovascular revascularization of the affected limb (median age 63.0 [60.0; 69.0] years) were studied. Microcirculation (MC) of the foot skin with assessment of nonlinear dynamic processes and spectral wavelet analysis of blood flow fluctuations was studied by laser Doppler flowmetry. The normalized amplitude indices of blood flow fluctuations were determined in frequency ranges reflecting: endothelial, neurogenic, myogenic, respiratory, pulse factors of hemocirculation. Bypass parameters and nutritive blood flow were assessed. An occlusion test was performed to determine capillary blood flow reserve. The study of nonlinear dynamic processes included assessment of fractal dimension, entropy determination and phase portrait analysis.
Results. Limb revascularization in patients with OALLA resulted in improvement of the clinical picture accompanied by statistically significant increase in nutritive blood flow (+9.7%) and reserved dilatation potential of microvessels (+43.2%), decrease in arteriolo-venular blood shunting (–5.0%) and venous plethora (–14.3%). The analysis of nonlinear dynamic processes of the MC showed that after angioplasty, along with the remaining deficit of oscillatory processes energy, there was a decrease in the fractal dimension index (–14.3%), indicating the limitation of lability of the functional system of the microvascular bed. At the same time, an increase in the chaotization of the regulatory mechanisms of the peripheral blood flow was established.
Conclusions. The results showed positive functional changes of the MC system associated with the improved clinical picture in patients with OALLA after limb revascularization. At the same time, changes in the nonlinear dynamics parameters indicate a compensatory increase in the chaotization of the system together with the remaining limitation of its functional lability and the energy deficit of oscillatory processes.
About the Authors
A. P. VasilievRussian Federation
Alexander P. Vasiliev - Dr. Sci. (Med.), Leading Research Scientist, Arterial Hypertension and Coronary Insufficienc Department, Scientific Department of Clinical Cardiology, Tyumen Cardiology Research Center, Tomsk National Research Medical Center, Russian Academy of Sciences.
111, Melnikaite str., Tyumen, 625026
N. N. Streltsova
Russian Federation
Nina N. Streltsova - Scientific Research Scientist, Department of Arterial Hypertension and Coronary Insufficien , Scientific Deparment of Clinical Cardiology, Tyumen Cardiology Research Center, Tomsk National Research Medical Center, Russian Academy of Sciences.
111, Melnikaite str., Tyumen, 625026
References
1. Beckman I.N. Nonlinear dynamics of complex systems: theory and practice. Metascience. The evolution of systems. Moscow; 2018. (In Russ.).
2. Bonato P., Roy S.H., Knaflitz M., De Luca C.J. Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions. IEEE Trans. Biomed. Eng. 2001; 48(7):745–53. DOI: 10.1109/10.930899.
3. Krupatkin A.I., Sidorov V.V. Functional diagnostics of mikrotsirkuljatornotissue systems: Fluctuations, information, nonlinearity. Guide for Physicians. Moscow: Librokom; 2013:496. (In Russ.).
4. Anishchenko V.S. Introduction to nonlinear dynamics. Moscow: LKI Publishing House; 2008:224. (In Russ.).
5. Klonowski W. From conformons to human brains: an informal overview of nonlinear dynamics and its applications in biomedicine. Nonlinear Biomed. Phys. 2007;1(1):5. DOI: 10.1186/1753-4631-1-5.
6. Henriques T., Ribeiro M., Teixeira A., Castro L., Antunes L., Costa-Santos C. Nonlinear Methods Most Applied to Heart-Rate Time Series: A Review. Entropy (Basel). 2020;22(3):309. DOI: 10.3390/e22030309.
7. Ilarraza-Lomelí H., Rius-Suárez M.D. Complexus cordis. Arch. Cardiol. Mex. 2020;91(3):327–336. DOI: 10.24875/ACM.200000391.
8. Ma Y., Shi W., Peng C.-K., Yang A.C. Nonlinear dynamical analysis of sleep electroencephalography using fractal and entropy approaches. Sleep. Med. Rev. 2018;37:85– 93. DOI: 10.1016/j.smrv.2017.01.003.
9. Zueva M.V. Nonlinear fractals: applications in physiology and ophthalmology. Zueva M.V. Nonlinear fractals: applications in physiology and ophthal. Ophthalmology in Russia. 2014; 11(1):4–11. (In Russ.).
10. Krupatkin A.I., Sidorov V.V., Kucherik A.O., Troitsky D.P. Modern possibilities to analyse the behavior of microhemocirculation as nonlinear dynamic system. Regional blood circulation and microcirculation. 2010;9(1):61–67. (In Russ.).
11. Kozhevnikova K.V., Malyuzhinskaya N.V., Polyakov O.V. Аnalysis of nonlinear dynamics in the microvasculature in children with type 1 diabetes by laser doppler flowmete . Journal of Volgograd state medical university. 2016;58(2):127–131. (In Russ.). URL: https://www.volgmed.ru/uploads/journals/articles/1494054472-vestnik-2016-2-2700.pdf (31.01.2023).
12. Streltsova N.N., Vasiliev A.P. Non-linear dynamic processes and their correlation with indicators of microcirculation in patients with obliterating atherosclerosis of the lower extremities arteries according to laser doppler flowmetr . Laser medicine. 2022;26(2):15–20. (In Russ.). DOI: 10.37895/2071-8004-2022-26-2-15-20.
13. Schmid-Schönbein H., Ziege S., Grebe R., Blazek V., Spielmann R., Linzenich F. Synergetic interpretation of patterned vasomotor activity in microvascuiar perfusion: discrete effects of myogenic and neurogenic vasoconstriction as well as arterial and venous pressure fluctuations. Int. J. Microcirc. Clin. Exp. 1997;17(6):346–59. DOI: 10.1159/000179251.
14. Muravyov A.V., Mikhailov P.V., Tikhomirova I.A. Microcirculation and hemorheology: points of interaction. Regional blood circulation and microcirculation. 2017;16(2):90–100. (In Russ.). DOI: 10.24884/1682-6655-2017-16-2-90-100.
15. Hamlin S.K., Benedik P.S. Basic concepts of hemorheology in microvascular hemodynamics. Crit. Care Nurs. Clin. North Am. 2014;26(3):337–44. DOI: 10.1016/j.ccell.2014.04.005.
16. Goldberg Eri L., Rigney D.R., West B.D. Chaos and fractals in human physiology. In the world of science. 1990;4:25–32. (In Russ.).
17. Isler V., Narin A., Ozer M., Perc M. Multi-stage classification of congestive heart failure basedon short-term heart rate variability. Chaos, Solitons & Fractals. 2019;118:145–151. DOI: 10.1016/j.chaos.2018.11.020.
18. Mondéjar-Guerra V., Novo J., Rouco J., Penedo M.G., Ortega M. Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers. Biomedical Signal Processing and Control. 2019;47:41–48. DOI: 10.1016/j.bspc.2018.08.007.
19. Skinner J.E., Pratt C.M., Vybiral T. A reduction in the correlation dimension of heartbeat intervals precedes imminent ventricular fibrill tion in human subjects. Am. Heart. J. 1993;125(3):731–743. DOI: 10.1016/0002-8703(93)90165-6.
Review
For citations:
Vasiliev A.P., Streltsova N.N. Changes in oscillatory and nonlinear dynamic processes of microcirculation in patients with obliterating atherosclerosis of lower limb arteries after revascularization. Siberian Journal of Clinical and Experimental Medicine. 2023;38(1):75-81. (In Russ.) https://doi.org/10.29001/2073-8552-2023-38-1-75-81