Abstract
Objective: The objective was to explore the validity of industry-parameterized vital signs in the generation of pressure reactivity index (PRx) and optimal cerebral perfusion pressure (CPPopt) values.
Materials and methods: Ten patients with intracranial pressure (ICP) monitors from 2008 to 2013 in a tertiary care hospital were included. Arterial blood pressure (ABP) and ICP were sampled at 240 Hz (of waveform data) and 0.2 Hz (of parameterized data produced by heuristic industry proprietary algorithms). 240-Hz ABP were filtered for pulse pressure and diastolic ABP within the limits of 20–150 mmHg. The PRx was calculated as Pearson’s correlation coefficient using 10-s averages of ICP and ABP over a 5-min moving window with 80% overlap. For ease of comparison, we used the naming convention of BMx for PRx values derived from 0.2-Hz data. A 5-min median cerebral perfusion pressure (CPP) trend was calculated, PRx or BMx values divided and averaged into CPP bins spanning 5 mmHg. The minimum Y value (PRx or BMx) of the parabolic function fit to the resulting XY plot of 4 h of data was obtained, and updated every 1 min. Pearson’s R correlations were calculated for each patient. Linear mixed-effects models were used with a random intercept to assess the overall correlation between the PRx (outcome) and the BMx (fixed effect) or the CPPopt-PRx (outcome) and the CPPopt-BMx (fixed effect).
Results: The overall correlation between the PRx and BMx was 0.78 based on the linear mixed effects models (p < 0.0001), and the overall correlation for the CPPopt–PRx and CPPopt–BMx based on the linear mixed effects models was 0.76 (p < 0.0001). One patient had low correlation of CPPopts derived from the PRx vs the BMx; this patient had the least number of hours of CPPopt data to compare.
Conclusions: The BMx shows promise in CPPopt derivation against the validated PRx measure. If further developed, it could expand the capability of centers to derive CPPopt goals for use in clinical trials.
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Acknowledgements
SP is supported by grant funding NIH K01 ES026833.
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Megjhani, M. et al. (2018). Deriving the PRx and CPPopt from 0.2-Hz Data: Establishing Generalizability to Bedmaster Users. In: Heldt, T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. https://doi.org/10.1007/978-3-319-65798-1_37
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