(Stroke. 1996;27:2236-2243.)
© 1996 American Heart Association, Inc.
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the Department of Neurosurgery (R.S., C.B., R.L., I.B., R.F.) and Institute of Physiology and Cardiology (R.D.B.), University of Erlangen-Nurnberg, Erlangen, and the Department of Medical Informatics, University of Heidelberg, Fachhochschule Heilbronn, Heilbronn (U.H.), Germany.
Background and Purpose Various biological signals show nonpulsatile, slow rhythmic oscillations. These include arterial blood pressure (aBP), blood flow velocity in cerebral arteries, intracranial pressure (ICP), cerebral microflow, and cerebral tissue PO2. Generation and interrelations between these rhythmic fluctuations remained unclear. The aim of this study was to analyze whether stable dynamic interrelations in the low-frequency range exist between these different variables, and if they do, to analyze their exact time delay.
Methods In a clinical study, 16 comatose patients with either higher-grade subarachnoid hemorrhage or severe traumatic brain injury were examined. A multimodal digital data acquisition system was used to simultaneously monitor aBP, flow velocity in the middle cerebral artery (FVMCA), ICP, cerebral microflow, and oxygen saturation in the jugular bulb (SjO2). Cross-correlation as a means to analyze time delay and correlation between two periodic signals was applied to a time series of 30 minutes' duration divided into four segments of 2048 data points (
436 seconds) each. This resulted in four cross-correlations for each 30-minute time series. If the four cross-correlations were consistent and reproducible, averaging of the original cross-correlations was performed, resulting in a representative time delay and correlation for the complete 30-minute interval.
Results Reproducible cross-correlations and stable dynamic interrelations were found between aBP, FVMCA, ICP, and SjO2. The mean time delay between aBP and ICP was 6.89±1.90 seconds, with a negative correlation in 81%. A mean time delay of 1.50±1.29 seconds (median, 0.85 seconds) was found between FVMCA and ICP, with a positive correlation in 94%. The mean delay between ICP and SjO2 was 9.47±2.21 seconds, with a positive correlation in 77%. Mean values of aBP and ICP did not influence the time delay and dynamic interrelation between the different parameters.
Conclusions These results strongly support Rosner's theory that ICP B-waves are the autoregulatory response of spontaneous fluctuations of cerebral perfusion pressure. There is casuistic evidence that failure of autoregulation significantly modifies time delay and the correlation between aBP and ICP.
Key Words: autoregulation blood pressure cerebral blood flow intracranial pressure
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