• Critical care medicine · Apr 2017

    Review Meta Analysis

    Predictors of Outcome With Cerebral Autoregulation Monitoring: A Systematic Review and Meta-Analysis.

    • Lucia Rivera-Lara, Andres Zorrilla-Vaca, Romer Geocadin, Wendy Ziai, Ryan Healy, Richard Thompson, Peter Smielewski, Marek Czosnyka, and Charles W Hogue.
    • 1Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD.2Department of Anesthesiology & Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD.3Department of Anesthesiology, Universidad del Valle, School of Medicine, Cali, Colombia.4Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.5Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
    • Crit. Care Med. 2017 Apr 1; 45 (4): 695-704.

    ObjectiveTo compare cerebral autoregulation indices as predictors of patient outcome and their dependence on duration of monitoring.Data SourcesSystematic literature search and meta-analysis using PubMed, EMBASE, and the Cochrane Library from January 1990 to October 2015.Study SelectionWe chose articles that assessed the association between cerebral autoregulation indices and dichotomized or continuous outcomes reported as standardized mean differences or correlation coefficients (R), respectively. Animal and validation studies were excluded.Data ExtractionTwo authors collected and assessed the data independently. The studies were grouped into two sets according to the type of analysis used to assess the relationship between cerebral autoregulation indices and predictors of outcome (standardized mean differences or R).Data SynthesisThirty-three studies compared cerebral autoregulation indices and patient outcomes using standardized mean differences, and 20 used Rs. The only data available for meta-analysis were from patients with traumatic brain injury or subarachnoid hemorrhage. Based on z score analysis, the best three cerebral autoregulation index predictors of mortality or Glasgow Outcome Scale for patients with traumatic brain injury were the pressure reactivity index, transcranial Doppler-derived mean velocity index based on cerebral perfusion pressure, and autoregulation reactivity index (z scores: 8.97, 6.01, 3.94, respectively). Mean velocity index based on arterial blood pressure did not reach statistical significance for predicting outcome measured as a continuous variable (p = 0.07) for patients with traumatic brain injury. For patients with subarachnoid hemorrhage, autoregulation reactivity index was the only cerebral autoregulation index that predicted patient outcome measured with the Glasgow Outcome Scale as a continuous outcome (R = 0.82; p = 0.001; z score, 3.39). We found a significant correlation between the duration of monitoring and predictive value for mortality (R = 0.78; p < 0.001).ConclusionsThree cerebral autoregulation indices, pressure reactivity index, mean velocity index based on cerebral perfusion pressure, and autoregulation reactivity index were the best outcome predictors for patients with traumatic brain injury. For patients with subarachnoid hemorrhage, autoregulation reactivity index was the only cerebral autoregulation index predictor of Glasgow Outcome Scale. Continuous assessment of cerebral autoregulation predicted outcome better than intermittent monitoring.

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