Analyses of cerebral microdialysis in patients with traumatic brain injury: relations to intracranial pressure, cerebral perfusion pressure and catheter placement.

BACKGROUND: Cerebral microdialysis (MD) is used to monitor local brain chemistry of patients with traumatic brain injury (TBI). Despite an extensive literature on cerebral MD in the clinical setting, it remains unclear how individual levels of real-time MD data are to be interpreted. Intracranial pressure (ICP) and cerebral perfusion pressure (CPP) are important continuous brain monitors in neurointensive care. They are used as surrogate monitors of cerebral blood flow and have an established relation to outcome. The purpose of this study was to investigate the relations between MD parameters and ICP and/or CPP in patients with TBI. METHODS: Cerebral MD, ICP and CPP were monitored in 90 patients with TBI. Data were extensively analyzed, using over 7,350 samples of complete (hourly) MD data sets (glucose, lactate, pyruvate and glycerol) to seek representations of ICP, CPP and MD that were best correlated. MD catheter positions were located on computed tomography scans as pericontusional or nonpericontusional. MD markers were analyzed for correlations to ICP and CPP using time series regression analysis, mixed effects models and nonlinear (artificial neural networks) computer-based pattern recognition methods. RESULTS: Despite much data indicating highly perturbed metabolism, MD shows weak correlations to ICP and CPP. In contrast, the autocorrelation of MD is high for all markers, even at up to 30 future hours. Consequently, subject identity alone explains 52% to 75% of MD marker variance. This indicates that the dominant metabolic processes monitored with MD are long-term, spanning days or longer. In comparison, short-term (differenced or Δ) changes of MD vs. CPP are significantly correlated in pericontusional locations, but with less than 1% explained variance. Moreover, CPP and ICP were significantly related to outcome based on Glasgow Outcome Scale scores, while no significant relations were found between outcome and MD. CONCLUSIONS: The multitude of highly perturbed local chemistry seen with MD in patients with TBI predominately represents long-term metabolic patterns and is weakly correlated to ICP and CPP. This suggests that disturbances other than pressure and/or flow have a dominant influence on MD levels in patients with TBI.

Extended analysis of early computed tomography scans of traumatic brain injured patients and relations to outcome.

Traumatic brain injury (TBI) is responsible for up to 45% of in-hospital trauma mortality. Computed tomography (CT) is central to acute TBI diagnostics, and millions of brain CT scans are conducted yearly worldwide. Though many studies have addressed individual predictors of outcome from findings on CT scans, few have done so from a multivariate perspective. As these parameters are interrelated in a complex manner, there is a need for a better understanding of them in this context. CT scans from 861 TBI patients were reviewed according to an extensive protocol. An extended analysis of CT parameters with respect to outcome was performed using linear and non-linear methods. We identified complex interactions and mutual information in many of the parameters. Variables predicting death differ from those predicting unfavorable versus favorable outcomes (Glasgow Outcome Scale scores of 1-3 versus 4-5 [GOS]). The most important parameter for prediction of unfavorable outcome is the magnitude of midline shift. In fact, this parameter, as a continuous variable, is by itself a better predictor and is better calibrated than the Marshall CT score, even for predicting death. In addition, hematoma volumes are nearly co-linear with midline shift and can be substituted for it. A score of traumatic subarachnoid/intraventricular blood components adds substantially to model calibration. A CT scoring system geared toward dichotomous GOS scores is suggested. CT parameters were found to add 6-10% additional estimated explained variance in the presence of the important clinical variables of age, Glasgow Coma Scale score, and pupillary response. Finally we present a practical clinical "rule of thumb" to help predict the probability of unfavorable outcome using clinical and CT variables.