Analysis of interactions between cardiovascular oscillations for discrimination of early vascular disorders in arterial hypertension and type 2 diabetes. (January 2023)

• Record Type: Journal Article
• Authors: Tikhonova, Irina V.; Tankanag, Arina V.; Guseva, Irina E.; Grinevich, Andrey A.
• Is Part Of: Biomedical signal processing and control. Volume 79(2023)Part 2
• Publication Date: 2023-01
• Subjects: Hypertension -- Diabetes mellitus -- Skin blood flow oscillations -- Heart rate variability -- Postural test -- External and internal couplings -- Wavelet phase coherence -- ROC-analysis; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2022.104222
• Languages: English
• ISSNs: 1746-8094

Abstract

Graphical abstract: Highlights: Comprehensive analysis of cardiovascular oscillations in hypertension and diabetes. High discriminative power of phase coherence to distinguish patients from controls. ROC-analysis of spectral component correlation discerned patients from controls. High discriminative power of spectral component correlation to differentiate pathologies. Abstract: Objective: Early identification of blood flow regulation disturbances allows developing new diagnostic methods for the predictive and personalized medicine in cardiovascular diseases. Comprehensive analysis of interactions between cardiovascular oscillations was proposed to reveal vascular disorders in arterial hypertension (AH) and type 2 diabetes mellitus (T2DM) patients. Methods: Heart rate variability (HRV), forearm and foot skin blood flow (SBF) were registered simultaneously at rest and under postural exposure in controls, AH and T2DM patients. Spectral components of signals, group wavelet phase coherence (gWPC) and Spearman's rank correlations were evaluated. Receiver Operating Characteristic curve analysis was applied to reveal the most effective predictors of cardiovascular system state. Results: In patients, spectral amplitudes of foot SBF was lower in low and high frequency ranges at rest and under postural test than forearm SBF. In controls these parameters were lower only in high frequency ranges versus forearm. HRV spectral components were lower at rest in T2DM and under test in all patients. For all signal pairs gWPC decreased in low frequency interval at rest and during test in patients. Correlations were higher on forearm in AH and on foot in T2DM during test. gWPC and correlations were the most effective to distinguish patients from controls. Correlations had high discriminative power to differentiate AH and T2DM patients. Conclusion: Analysis of interactions between cardiovascular oscillations can be used as an effective instrument for clinical application in prognosis and diagnosis of early pathophysiological changes in cardiovascular system in response to various exposure and under different pathologies.