Literature DB >> 18080759

Arterial baroreflexes and cardiovascular modeling.

Dwain L Eckberg1.   

Abstract

Many cardiovascular models involve prediction of changes that occur when a subject is perturbed in some way, to move from one state to another. A successful, predictive model should involve at least two elements: First, the model should include some index of the intensity of the perturbation that elicits the response; effective responses should, in some fashion, be linearly or nonlinearity related to perturbations. Second, the model should factor in subjects' abilities to meet the challenges posed by the perturbations. This review indicates that these two basic components of a successful model may be difficult to incorporate. In the simple case of passive upright tilt, blood pressure measurements may not accurately indicate the stimulus, because blood pressure reductions are reversed by rapidly occurring reflex blood pressure increases. Since not all subject populations respond identically to hemodynamic challenges, it also may be important to characterize baroreflex responsiveness, and include such a term in a model. Although vagal and sympathetic baroreflex responses to stereotyped challenges can be measured accurately, recent research points to extraordinary variability of baroreflex responsiveness. The complexities discussed in this review should be considered, whether they are, or even can be incorporated into cardiovascular models.

Mesh:

Year:  2008        PMID: 18080759     DOI: 10.1007/s10558-007-9042-8

Source DB:  PubMed          Journal:  Cardiovasc Eng        ISSN: 1567-8822


  5 in total

1.  Assessment of Baroreflex Control of Heart Rate During General Anesthesia Using a Point Process Method.

Authors:  Z Chen; Pl Purdon; Et Pierce; G Harrell; En Brown; R Barbieri
Journal:  Proc IEEE Int Conf Acoust Speech Signal Process       Date:  2009-05-26

2.  Identifying physiological origins of baroreflex dysfunction in salt-sensitive hypertension in the Dahl SS rat.

Authors:  Scott M Bugenhagen; Allen W Cowley; Daniel A Beard
Journal:  Physiol Genomics       Date:  2010-03-30       Impact factor: 3.107

3.  Dynamic assessment of baroreflex control of heart rate during induction of propofol anesthesia using a point process method.

Authors:  Zhe Chen; Patrick L Purdon; Grace Harrell; Eric T Pierce; John Walsh; Emery N Brown; Riccardo Barbieri
Journal:  Ann Biomed Eng       Date:  2010-10-13       Impact factor: 3.934

4.  A Point Process Approach to Assess Dynamic Baroreflex Gain.

Authors:  Z Chen; En Brown; R Barbieri
Journal:  Comput Cardiol       Date:  2008-09-14

5.  A unified point process probabilistic framework to assess heartbeat dynamics and autonomic cardiovascular control.

Authors:  Zhe Chen; Patrick L Purdon; Emery N Brown; Riccardo Barbieri
Journal:  Front Physiol       Date:  2012-02-01       Impact factor: 4.566

  5 in total

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