OBJECTIVE: Computer-assisted analysis of neuromonitoring parameters may provide important decision-making support to the neurointensivist. A recently developed mathematical model for the simulation of cerebral autoregulation and brain swelling showed that in the case of an intact autoregulation but diminished cerebral compliance, a negative correlation between arterial blood pressure (ABP) and intracranial pressure (ICP) occurs. The goal of our study was to verify these simulation results in an appropriate patient cohort. METHODS: Simultaneously measured data (ABP, ICP) of 6 patients (1 female; 5 male) with severe head trauma (n = 5) and stroke (n = 1) were used to calculate time resolved multitaper cross coherence. Further, we calculated the Hilbert phases of both signals, defining a negative correlation in case of a mean Hilbert phase difference greater than 130°. To validate the results, CT scans performed during the critical phases identified were analyzed. RESULTS: In five out of six datasets we found long lasting events of negative correlation between ABP and ICP. In all patients, corresponding CT scans demonstrated changes in the intracranial compartment characterized by diminished cerebral compliance. CONCLUSIONS: Our data indicate that complex multidimensional data analysis of neuromonitoring parameters can identify complication-specific data patterns with a high degree of accuracy.
OBJECTIVE: Computer-assisted analysis of neuromonitoring parameters may provide important decision-making support to the neurointensivist. A recently developed mathematical model for the simulation of cerebral autoregulation and brain swelling showed that in the case of an intact autoregulation but diminished cerebral compliance, a negative correlation between arterial blood pressure (ABP) and intracranial pressure (ICP) occurs. The goal of our study was to verify these simulation results in an appropriate patient cohort. METHODS: Simultaneously measured data (ABP, ICP) of 6 patients (1 female; 5 male) with severe head trauma (n = 5) and stroke (n = 1) were used to calculate time resolved multitaper cross coherence. Further, we calculated the Hilbert phases of both signals, defining a negative correlation in case of a mean Hilbert phase difference greater than 130°. To validate the results, CT scans performed during the critical phases identified were analyzed. RESULTS: In five out of six datasets we found long lasting events of negative correlation between ABP and ICP. In all patients, corresponding CT scans demonstrated changes in the intracranial compartment characterized by diminished cerebral compliance. CONCLUSIONS: Our data indicate that complex multidimensional data analysis of neuromonitoring parameters can identify complication-specific data patterns with a high degree of accuracy.
Authors: Rupert Faltermeier; Martin A Proescholdt; Sylvia Bele; Alexander Brawanski Journal: Comput Math Methods Med Date: 2015-03-03 Impact factor: 2.238
Authors: Rupert Faltermeier; Martin A Proescholdt; Sylvia Bele; Alexander Brawanski Journal: Comput Math Methods Med Date: 2015-11-29 Impact factor: 2.238
Authors: Martin A Proescholdt; Rupert Faltermeier; Sylvia Bele; Alexander Brawanski Journal: Comput Math Methods Med Date: 2017-01-31 Impact factor: 2.238
Authors: Rupert Faltermeier; Martin A Proescholdt; Stefan Wolf; Sylvia Bele; Alexander Brawanski Journal: Comput Math Methods Med Date: 2018-08-08 Impact factor: 2.238