EconPapers    
Economics at your fingertips  
 

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Kun Hu, C.K. Peng, Norden E. Huang, Zhaohua Wu, Lewis A. Lipsitz, Jerry Cavallerano and Vera Novak

Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, issue 10, 2279-2292

Abstract: Cerebral autoregulation is an important mechanism that involves dilatation and constriction in arterioles to maintain relatively stable cerebral blood flow in response to changes of systemic blood pressure. Traditional assessments of autoregulation focus on the changes of cerebral blood flow velocity in response to large blood pressure fluctuations induced by interventions. This approach is not feasible for patients with impaired autoregulation or cardiovascular regulation. Here we propose a newly developed technique—the multimodal pressure-flow (MMPF) analysis, which assesses autoregulation by quantifying nonlinear phase interactions between spontaneous oscillations in blood pressure and flow velocity during resting conditions. We show that cerebral autoregulation in healthy subjects can be characterized by specific phase shifts between spontaneous blood pressure and flow velocity oscillations, and the phase shifts are significantly reduced in diabetic subjects. Smaller phase shifts between oscillations in the two variables indicate more passive dependence of blood flow velocity on blood pressure, thus suggesting impaired cerebral autoregulation. Moreover, the reduction of the phase shifts in diabetes is observed not only in previously-recognized effective region of cerebral autoregulation (<0.1 Hz), but also over the higher frequency range from ∼0.1 to 0.4 Hz. These findings indicate that type 2 diabetes mellitus alters cerebral blood flow regulation over a wide frequency range and that this alteration can be reliably assessed from spontaneous oscillations in blood pressure and blood flow velocity during resting conditions. We also show that the MMPF method has better performance than traditional approaches based on Fourier transform, and is more suitable for the quantification of nonlinear phase interactions between nonstationary biological signals such as blood pressure and blood flow.

Keywords: Nonstationary; Nonlinear phase interaction; Instantaneous phase shift; Cerebral autoregulation; Cerebral blood flow velocity; Multimodal pressure-flow analysis (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437107012605
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:387:y:2008:i:10:p:2279-2292

DOI: 10.1016/j.physa.2007.11.052

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:phsmap:v:387:y:2008:i:10:p:2279-2292