An optimal frequency range for assessing the pressure reactivity index in patients with traumatic brain injury
Journal article, 2015

The objective of this study was to identify the optimal frequency range for computing the pressure reactivity index (PRx). PRx is a clinical method for assessing cerebral pressure autoregulation based on the correlation of spontaneous variations of arterial blood pressure (ABP) and intracranial pressure (ICP). Our hypothesis was that optimizing the methodology for computing PRx in this way could produce a more stable, reliable and clinically useful index of autoregulation status. The patients studied were a series of 131 traumatic brain injury patients. Pressure reactivity indices were computed in various frequency bands during the first 4 days following injury using bandpass filtering of the input ABP and ICP signals. Patient outcome was assessed using the extended Glasgow Outcome Scale (GOSe). The optimization criterion was the strength of the correlation with GOSe of the mean index value over the first 4 days following injury. Stability of the indices was measured as the mean absolute deviation of the minute by minute index value from 30-min moving averages. The optimal index frequency range for prediction of outcome was identified as 0.018-0.067 Hz (oscillations with periods from 55 to 15 s). The index based on this frequency range correlated with GOSe with ρ = -0.46 compared to -0.41 for standard PRx, and reduced the 30-min variation by 23 %. © 2014 Springer Science+Business Media New York.

Cerebral perfusion pressure

Cerebral pressure autoregulation

Optimization

Clinical monitoring

Intracranial pressure

Author

T.P. Howells

Uppsala University

U. Johnson

Uppsala University

Tomas McKelvey

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

P. Enblad

Uppsala University

Journal of Clinical Monitoring and Computing

1387-1307 (ISSN) 1573-2614 (eISSN)

Vol. 29 1 97-105

Areas of Advance

Information and Communication Technology

Life Science Engineering (2010-2018)

Subject Categories

Signal Processing

DOI

10.1007/s10877-014-9573-7

More information

Latest update

10/5/2021