Assessment of cerebral autoregulation indices – a modelling perspective
Autor: | Xiuyun Liu, Manuel Cabeleira, Joseph Donnelly, Danilo Cardim, Despina Aphroditi Lalou, Peter J. Hutchinson, Xiao Hu, Marek Czosnyka, Peter Smielewski |
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Přispěvatelé: | Donnelly, Joseph [0000-0002-6502-8069], Lalou, Despina Aphroditi [0000-0003-3768-8681], Smielewski, Peter [0000-0001-5096-3938], Apollo - University of Cambridge Repository |
Rok vydání: | 2020 |
Předmět: |
Adult
Male medicine.medical_specialty Correlation coefficient Models Neurological lcsh:Medicine 030204 cardiovascular system & hematology Cerebral autoregulation Article 03 medical and health sciences 0302 clinical medicine Internal medicine Brain Injuries Traumatic Dynamical systems medicine Homeostasis Humans Autoregulation Very low frequency lcsh:Science 692/308/1426 Cerebrum Mathematics Multidisciplinary 692/617 lcsh:R Confounding 119/118 Experimental models of disease 631/378/116/2393 Noise Neurology Cerebral blood flow Colors of noise Cerebrovascular Circulation Cardiology lcsh:Q Female 030217 neurology & neurosurgery |
Zdroj: | Scientific Reports Scientific Reports, Vol 10, Iss 1, Pp 1-11 (2020) |
ISSN: | 2045-2322 |
DOI: | 10.1038/s41598-020-66346-6 |
Popis: | Various methodologies to assess cerebral autoregulation (CA) have been developed, including model - based methods (e.g. autoregulation index, ARI), correlation coefficient - based methods (e.g. mean flow index, Mx), and frequency domain - based methods (e.g. transfer function analysis, TF). Our understanding of relationships among CA indices remains limited, partly due to disagreement of different studies by using real physiological signals, which introduce confounding factors. The influence of exogenous noise on CA parameters needs further investigation. Using a set of artificial cerebral blood flow velocities (CBFV) generated from a well-known CA model, this study aims to cross-validate the relationship among CA indices in a more controlled environment. Real arterial blood pressure (ABP) measurements from 34 traumatic brain injury patients were applied to create artificial CBFVs. Each ABP recording was used to create 10 CBFVs corresponding to 10 CA levels (ARI from 0 to 9). Mx, TF phase, gain and coherence in low frequency (LF) and very low frequency (VLF) were calculated. The influence of exogenous noise was investigated by adding three levels of colored noise to the artificial CBFVs. The result showed a significant negative relationship between Mx and ARI (r = −0.95, p |
Databáze: | OpenAIRE |
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