4.6 Article

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

Journal

CRITICAL CARE MEDICINE
Volume 45, Issue 4, Pages 695-704

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/CCM.0000000000002251

Keywords

cerebral blood flow; cerebrovascular autoregulation; intracranial pressure monitoring; neuromonitoring; transcranial Doppler

Funding

  1. Johns Hopkins Institute for Clinical and Translational Research (ICTR)
  2. National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH) [UL1 TR 000424-06]
  3. NIH Roadmap for Medical Research
  4. National Institutes of Health (NIH)
  5. NIH [R01 HL 92259]
  6. American Academy of Neurology/American Brain Foundation
  7. Covidien
  8. Medtronic/Covidien, Dublin, IR
  9. Cambridge Enterprise
  10. Integra Speakers Bureau
  11. MRC [G0600986] Funding Source: UKRI
  12. Medical Research Council [G0600986] Funding Source: researchfish

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Objective: To compare cerebral autoregulation indices as predictors of patient outcome and their dependence on duration of monitoring. Data Sources: Systematic literature search and meta-analysis using PubMed, EM BASE, and the Cochrane Library from January 1990 to October 2015. Study Selection: We 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 Extraction: Two 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 Synthesis: Thirty-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). Conclusions: Three 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 subarabhnoid 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. (Crit Care Med 2017; 45:695-704)

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