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. 2015;2015:534-7.
doi: 10.1109/EMBC.2015.7318417.

An Enhanced Cerebral Recovery Index for Coma Prognostication Following Cardiac Arrest

Free PMC article

An Enhanced Cerebral Recovery Index for Coma Prognostication Following Cardiac Arrest

Mohammad M Ghassemi et al. Conf Proc IEEE Eng Med Biol Soc. .
Free PMC article

Abstract

Prognostication of coma outcomes following cardiac arrest is both qualitative and poorly understood in current practice. Existing quantitative metrics are powerful, but lack rigorous approaches to classification. This is due, in part, to a lack of available data on the population of interest. In this paper we describe a novel retrospective data set of 167 cardiac arrest patients (spanning three institutions) who received electroencephalography (EEG) monitoring. We utilized a subset of the collected data to generate features that measured the connectivity, complexity and category of EEG activity. A subset of these features was included in a logistic regression model to estimate a dichotomized cerebral performance category score at discharge. We compared the predictive performance of our method against an established EEG-based alternative, the Cerebral Recovery Index (CRI) and show that our approach more reliably classifies patient outcomes, with an average increase in AUC of 0.27.

Figures

Figure 1
Figure 1
The original CRI. The blue line signifies patients with positive neurological outcomes (CPC <=2), and the red line signifies patients with negative neurological outcomes (CPC >=3). Shaded areas represent the standard error of the sample.
Figure 2
Figure 2
Our enhanced CRI. The blue line signifies patient with positive neurological outcomes (CPC <=2), and the red line signifies patients with negative neurological outcomes (CPC >=3). Shaded areas represent standard error of the sample.
Figure 3
Figure 3
Comparison of overall classification performance overtime for the CRI, eCRI, and CRI’s compliment.

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