gms | German Medical Science

Objective: In neurocritical care, it is crucial to detect pathophysiological conditions such as reduced intracranial compliance or impaired cerebral autoregulation as early as possible. To achieve this goal, an array of different brain monitoring techniques was established. However, focusing on specific parameters with fixed thresholds may not be adequate for finding the optimal treatment algorithm. In contrast, it is necessary to integrate the multimodal monitoring data into a platform making it possible to unmask critical changes in intracranial dynamics. We therefore developed a point of care system, which allows the detection of brain swelling and impairment of autoregulation, based on model simulations that predict specific correlation between ABP and ICP under the above mentioned pathophysiological conditions.

Methods: Initially, we developed a mathematical toolkit called selected correlation analysis (sca) that reliably detects negative and positive correlations between arterial blood pressure (ABP) and intracranial pressure (ICP) data. To identify slow homeostatic positive or negative correlations between isochronic segments of ABP and ICP, we utilized coherence and power spectra calculations (lsc) with the multi-taper method (MTM). In addition, we calculated the mean Hilbert phase difference between these segments (mhpd). If mhpd is higher or equal to 110 degree a correlation is called negative (scn) and indicates reduced intracranial compliance without loss of autoregulation. Conversely if the mhpd is lower or equal 70 degree, the correlation is defined as called positive (scp) and therefore suggests an impaired autoregulation. Finally, we established a method that detects the rate of false positives for fixed pairs of thresholds (lsc,lmhpd), to determine a valid significance level for all future patients.

Results: We calculated the error rates as a function of the predefined thresholds for each individual out of a patient cohort of 52 patients in a retrospective way. We subsequently incorporated these results into an analytical software platform, which has now been applied in four test patients. Our preliminary experience indicates a robust and stable detection of reduced intracranial compliance and/or impaired cerebral autoregulation.

Conclusion: Our data demonstrate that an integrated real time analysis tool to process brain multimodal monitoring data may be useful for the early detection and management of pathophysiological events.