Literature DB >> 10657425

Assessment of the thigh cuff technique for measurement of dynamic cerebral autoregulation.

P J Mahony1, R B Panerai, S T Deverson, P D Hayes, D H Evans.   

Abstract

BACKGROUND AND
PURPOSE: Dynamic methods of measuring cerebral autoregulation have become an accepted alternative to static evaluation. This article aims to describe a set of data collected from healthy volunteers by a dynamic method, the purpose being to qualify and quantify expected results for those who may be designing a study using this technique.
METHODS: Cerebral blood flow velocity (CBFV) (measured by transcranial Doppler) and arterial blood pressure (Finapres) were recorded in 16 normal subjects before, during, and after the induction of a blood pressure drop (release of bilateral thigh cuffs). This procedure was repeated 6 times for each subject. A mathematical model was applied to the data to generate an autoregulatory index (ARI) with values between 0 and 9.
RESULTS: The ARI values for this sample population follow a normal distribution, with a mean+/-SD of 4.98+/-1.06 (n=15). Analysis of the cumulative mean ARI values of all subjects showed an exponential-type convergence of ARI toward the sample mean as the number of test iterations increased. The population average blood pressure drop on thigh cuff release was 26.4+/-7.1 mm Hg (n=16), occurring in 4.6+/-1. 7 seconds. The corresponding population average drop for CBFV was 15. 6+/-5.8 cm/s, taking 2.5+/-1.0 seconds. No significant trend was noted in the measurements as the number of test iterations increased. The correlation between the predicted and actual CBFV, having a mean value of 0.76+/-0.19, showed evidence of a nonlinear relationship to ARI values. Significant correlation was also found between ARI and (1) arterial blood pressure before cuff release and (2) the magnitude of the drop in CBFV on cuff release.
CONCLUSIONS: The distribution of ARI values is not significantly different from normal. At least 3 iterations of the test procedure should be performed and averaged to obtain the mean ARI for each subject. There is no significant evidence of physiological accommodation as the number of test iterations increases. The effects of mean blood pressure and the magnitude of the change in CBFV should be considered as possible covariates when ARI data are analyzed.

Entities:  

Mesh:

Year:  2000        PMID: 10657425     DOI: 10.1161/01.str.31.2.476

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  22 in total

1.  Continuous monitoring of cerebrovascular autoregulation: a validation study.

Authors:  E W Lang; H M Mehdorn; N W C Dorsch; M Czosnyka
Journal:  J Neurol Neurosurg Psychiatry       Date:  2002-05       Impact factor: 10.154

2.  Spectral indices of human cerebral blood flow control: responses to augmented blood pressure oscillations.

Authors:  J W Hamner; Michael A Cohen; Seiji Mukai; Lewis A Lipsitz; J Andrew Taylor
Journal:  J Physiol       Date:  2004-07-14       Impact factor: 5.182

3.  Measurement of cerebral blood flow responses to the thigh cuff maneuver: a comparison of TCD with a novel MRI method.

Authors:  Nazia P Saeed; Mark A Horsfield; Ronney B Panerai; Amit K Mistri; Tom G Robinson
Journal:  J Cereb Blood Flow Metab       Date:  2010-12-29       Impact factor: 6.200

4.  Dynamic cerebral autoregulation following acute ischaemic stroke: Comparison of transcranial Doppler and magnetic resonance imaging techniques.

Authors:  Ronney B Panerai; José L Jara; Nazia P Saeed; Mark A Horsfield; Thompson G Robinson
Journal:  J Cereb Blood Flow Metab       Date:  2015-11-05       Impact factor: 6.200

5.  Analysis of dynamic autoregulation assessed by the cuff deflation method.

Authors:  Roman Hlatky; Alex B Valadka; Claudia S Robertson
Journal:  Neurocrit Care       Date:  2006       Impact factor: 3.210

6.  Dynamic cerebral autoregulation: different signal processing methods without influence on results and reproducibility.

Authors:  Erik D Gommer; Eri Shijaku; Werner H Mess; Jos P H Reulen
Journal:  Med Biol Eng Comput       Date:  2010-11-04       Impact factor: 2.602

7.  Methodological comparison of active- and passive-driven oscillations in blood pressure; implications for the assessment of cerebral pressure-flow relationships.

Authors:  Jonathan D Smirl; Keegan Hoffman; Yu-Chieh Tzeng; Alex Hansen; Philip N Ainslie
Journal:  J Appl Physiol (1985)       Date:  2015-07-16

8.  Detection of impaired cerebral autoregulation improves by increasing arterial blood pressure variability.

Authors:  Emmanuel Katsogridakis; Glen Bush; Lingke Fan; Anthony A Birch; David M Simpson; Robert Allen; John F Potter; Ronney B Panerai
Journal:  J Cereb Blood Flow Metab       Date:  2012-12-12       Impact factor: 6.200

9.  Dynamic Autoregulatory Response After Aneurysmal Subarachnoid Hemorrhage and Its Relation to Angiographic Vasospasm and Clinical Outcome.

Authors:  Johann Fontana; Julius Moratin; Gregory Ehrlich; Johann Scharf; Christel Weiß; Kirsten Schmieder; Martin Barth
Journal:  Neurocrit Care       Date:  2015-12       Impact factor: 3.210

Review 10.  Integrative physiological and computational approaches to understand autonomic control of cerebral autoregulation.

Authors:  Can Ozan Tan; J Andrew Taylor
Journal:  Exp Physiol       Date:  2013-10-04       Impact factor: 2.969

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