Abstract

ObjectiveEarly 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. MethodsHeart 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. ResultsIn 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. ConclusionAnalysis 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.

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