title: Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.
abstract: Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.
authors.affiliation: Department of Neurosurgery, University Hospital Regensburg, Regensburg, Germany.
authors.forename: Martin A
authors.identifier: 0000-0001-9284-0282
authors.initials: MA
authors.lastname: Proescholdt
authors.affiliation: Department of Neurosurgery, University Hospital Regensburg, Regensburg, Germany.
authors.forename: Rupert
authors.identifier: 0000-0003-4658-6433
authors.initials: R
authors.lastname: Faltermeier
authors.affiliation: Department of Neurosurgery, University Hospital Regensburg, Regensburg, Germany.
authors.forename: Sylvia
authors.identifier: 0000-0001-9887-3165
authors.initials: S
authors.lastname: Bele
authors.affiliation: Department of Neurosurgery, University Hospital Regensburg, Regensburg, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Brawanski
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D001794:Blood Pressure / Q000502:physiology; D001921:Brain / Q000502:physiology*; D000070642:Brain Injuries, Traumatic / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D002560:Cerebrovascular Circulation / Q000502:physiology; D003198:Computer Simulation; D005260:Female; D015600:Glasgow Coma Scale; D006706:Homeostasis / Q000502:physiology; D006801:Humans; D007427:Intracranial Pressure / Q000502:physiology; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity; D012984:Software; D013345:Subarachnoid Hemorrhage / Q000000981:diagnostic imaging*; D055815:Young Adult