Pain-related Somato Sensory Evoked Potentials: A potential new tool to improve the prognostic prediction of coma after cardiac arrest

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Abstract

Introduction: Early prediction of a good outcome in comatose patients after cardiac arrest still remains an unsolved problem. The main aim of the present study was to examine the accuracy of middle-latency SSEP triggered by a painful electrical stimulation on median nerves to predict a favorable outcome. Methods: No- and low-flow times, pupillary reflex, Glasgow motor score and biochemical data were evaluated at ICU admission. The following were considered within 72h of cardiac arrest: highest creatinine value, hyperthermia occurrence, EEG, SSEP at low- (10mA) and high-intensity (50mA) stimulation, and blood pressure reactivity to 50mA. Intensive care treatments were also considered. Data were compared to survival, consciousness recovery and 6-month CPC (Cerebral Performance Category). Results: Pupillary reflex and EEG were statistically significant in predicting survival; the absence of blood pressure reactivity seems to predict brain death within 7days of cardiac arrest. Middle- and short-latency SSEP were statistically significant in predicting consciousness recovery, and middle-latency SSEP was statistically significant in predicting 6-month CPC outcome. The prognostic capability of 50mA middle-latency-SSEP was demonstrated to occur earlier than that of EEG reactivity. Conclusions: Neurophysiological evaluation constitutes the key to early information about the neurological prognostication of postanoxic coma. In particular, the presence of 50mA middle-latency SSEP seems to be an early and reliable predictor of good neurological outcome, and its absence constitutes a marker of poor prognosis. Moreover, the absence 50mA blood pressure reactivity seems to identify patients evolving towards the brain death.

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Zanatta, P., Linassi, F., Mazzarolo, A. P., Aricò, M., Bosco, E., Bendini, M., … Scarpa, B. (2015). Pain-related Somato Sensory Evoked Potentials: A potential new tool to improve the prognostic prediction of coma after cardiac arrest. Critical Care, 19(1). https://doi.org/10.1186/s13054-015-1119-y

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