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Published on: January 5, 2018
Combination of Clinical Exam, MRI and EEG to Predict Outcome Following Cardiac Arrest and Targeted Temperature
Matthew B Bevers1, Benjamin M Scirica2, Kathleen Ryan Avery3
1Divisions of Stroke, Cerebrovascular and Critical Care Neurology, Brigham and Women's Hospital, Boston, MA, USA. mbevers@bwh.harvard.edu.
Background:
Despite the widespread adoption of targeted temperature management (TTM), coma after cardiac arrest remains a common problem with a high proportion of patients suffering substantial disability. Prognostication after cardiac arrest, particularly the identification of patients with likely good outcome, remains difficult.
Methods:
We performed a retrospective study of 78 patients who underwent TTM after cardiac arrest and were evaluated with both electroencephalography (EEG) and magnetic resonance imaging (MRI). We hypothesized that combining malignant versus non-malignant EEG classification with clinical exam and quantitative analysis of apparent diffusion coefficient (ADC) and fluid-attenuated inversion recovery imaging would improve prognostic ability.
Results:
Consistent with prior literature, presence of a malignant EEG pattern was 100% specific for poor outcome. We found that decreased whole brain ADC signal intensity was associated with poor outcome (853 ± 14 vs. 950 ± 17.5 mm2/s, p < 0.0001). Less than 15% total brain volume with ADC signal intensity < 650 mm2/s was predictive of good outcome with 100% sensitivity, 51% specificity and an area under the curve of 0.787. A model combining this ADC marker with non-malignant EEG and flexor-or-better motor response was 100% sensitive and 91.1% specific for good outcome following cardiac arrest and targeted temperature management.
Conclusion:
We conclude that in the absence of malignant EEG findings, combination of physical exam and MRI findings can be a useful to identify those patients who have potential for recovery. Variability in timing of imaging and findings in different modalities argue for the need for future prospective studies of multimodal outcome prediction after cardiac arrest.
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