To compare cerebral autoregulation indices as predictors of patient outcome and their dependence on duration of monitoring.
Systematic literature search and meta-analysis using PubMed, EMBASE, and the Cochrane Library from January 1990 to October 2015.
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.
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).
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).
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 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.
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.
*See also p. 751.
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Supported by the Johns Hopkins Institute for Clinical and Translational Research (ICTR), which is funded in part by Grant Number UL1 TR 000424-06 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the Johns Hopkins ICTR, NCATS, or NIH.
Dr. Rivera-Lara received support for article research from the National Institutes of Health (NIH). Her institution received funding (Dr. Hogue is the PI on an NIH-sponsored clinical study [R01 HL 92259]; Dr. Rivera-Lara is the PI on an American Academy of Neurology/American Brain Foundation and Covidien grant; and Dr. Hogue receives research funding from Medtronic/Covidien, Dublin, IR, and he serves as a consultant to Medtronic/Covidien and Ornim Medical, Foxborough, MA). Dr. Healy received support for article research from the NIH. Dr. Thompson received support for article research from the NIH. Dr. Smielewski disclosed other support (The author receives part of licensing fees of the software ICM+ used for data collection and partial analysis). Dr. Czosnyka received support for article research from Research Councils UK and received funding from Cambridge Enterprise and from Integra Speakers Bureau. Dr. Hogue received support for article research from the NIH and disclosed off-label product use (The autoregulation methods described are investigational but derived from Food and Drug Administration approved monitors). The remaining authors have disclosed that they do not have any potential conflicts of interest.
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