Literature DB >> 11474643

Nonlinear dynamics applied to blood pressure control.

S Eyal1, Y Almog, O Oz, S Eliash, S Akselrod.   

Abstract

Hypertension is a very frequent disease, known to trigger a range of severe cardiovascular problems. The elucidation of its pathophysiology requires investigation of the mechanisms responsible for the maintenance of blood pressure in the normal system, and their possible failure in hypertension. Some of these control mechanisms display nonlinear features, indicating that the blood pressure signal might be characterized by nonlinear dynamics. Our aim was thus to investigate the nonlinear properties of the blood pressure signal under normal conditions, and in a cardiovascular system prone to hypertension. Blood pressure was investigated in young spontaneously hypertensive rats (SHR), versus their age-matched normotensive progenitors (WKY). The correlation dimension was computed as quantification of blood pressure control complexity. The parameters required for the calculation procedure of the correlation dimension were carefully determined. The results were tested with surrogate data statistics. assuming linear autocorrelated Gaussian noise as the null hypothesis. Non-integer correlation dimension values were found in both strains, with lower values for SHR than for WKY, in particular following alpha-blockade. In all cases, a statistically significant difference was found between the real and surrogate data. These results show that the nonlinear dynamics parameter D, can be used to detect differences in BP control between prehypertensive SHR and WKY rats as early as 6-7 weeks after birth.

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Year:  2001        PMID: 11474643     DOI: 10.1016/S1566-0702(01)00249-1

Source DB:  PubMed          Journal:  Auton Neurosci        ISSN: 1566-0702            Impact factor:   3.145


  1 in total

1.  The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S).

Authors:  Irwin Gratz; Martin Baruch; Magdy Takla; Julia Seaman; Isabel Allen; Brian McEniry; Edward Deal
Journal:  BMC Anesthesiol       Date:  2020-05-01       Impact factor: 2.217

  1 in total

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