Comparison of high versus low frequency cerebral physiology for cerebrovascular reactivity assessment in traumatic brain injury: a multi-center pilot study

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http://hdl.handle.net/10138/318579

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Thelin , E P , Raj , R , Bellander , B-M , Nelson , D , Piippo-Karjalainen , A , Siironen , J , Tanskanen , P , Hawryluk , G , Hasen , M , Unger , B & Zeiler , F A 2020 , ' Comparison of high versus low frequency cerebral physiology for cerebrovascular reactivity assessment in traumatic brain injury: a multi-center pilot study ' , Journal of Clinical Monitoring and Computing , vol. 34 , no. 5 , pp. 971-994 . https://doi.org/10.1007/s10877-019-00392-y

Title: Comparison of high versus low frequency cerebral physiology for cerebrovascular reactivity assessment in traumatic brain injury: a multi-center pilot study
Author: Thelin, Eric P.; Raj, Rahul; Bellander, Bo-Michael; Nelson, David; Piippo-Karjalainen, Anna; Siironen, Jari; Tanskanen, Päivi; Hawryluk, Gregory; Hasen, Mohammed; Unger, Bertram; Zeiler, Frederick A.
Contributor: University of Helsinki, HUS Neurocenter
University of Helsinki, HUS Neurocenter
University of Helsinki, Neurokirurgian yksikkö
University of Helsinki, Department of Diagnostics and Therapeutics
Date: 2020-10
Language: eng
Number of pages: 24
Belongs to series: Journal of Clinical Monitoring and Computing
ISSN: 1573-2614
URI: http://hdl.handle.net/10138/318579
Abstract: Current accepted cerebrovascular reactivity indices suffer from the need of high frequency data capture and export for post-acquisition processing. The role for minute-by-minute data in cerebrovascular reactivity monitoring remains uncertain. The goal was to explore the statistical time-series relationships between intra-cranial pressure (ICP), mean arterial pressure (MAP) and pressure reactivity index (PRx) using both 10-s and minute data update frequency in TBI. Prospective data from 31 patients from 3 centers with moderate/severe TBI and high-frequency archived physiology were reviewed. Both 10-s by 10-s and minute-by-minute mean values were derived for ICP and MAP for each patient. Similarly, PRx was derived using 30 consecutive 10-s data points, updated every minute. While long-PRx (L-PRx) was derived via similar methodology using minute-by-minute data, with L-PRx derived using various window lengths (5, 10, 20, 30, 40, and 60 min; denoted L-PRx_5, etc.). Time-series autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) models were created to analyze the relationship of these parameters over time. ARIMA modelling, Granger causality testing and VARIMA impulse response function (IRF) plotting demonstrated that similar information is carried in minute mean ICP and MAP data, compared to 10-s mean slow-wave ICP and MAP data. Shorter window L-PRx variants, such as L-PRx_5, appear to have a similar ARIMA structure, have a linear association with PRx and display moderate-to-strong correlations (r ~ 0.700, p 
Subject: 3126 Surgery, anesthesiology, intensive care, radiology
Autoregulation
Cerebrovascular reactivity
Low-frequency
TBI
PERFUSION-PRESSURE
LOWER LIMIT
PART II
AUTOREGULATION
MICRODIALYSIS
VALIDATION
MANAGEMENT
CHEMISTRY
INDEXES
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