M.C. Cloostermans

Continuous electroencephalography monitoring for early prediction of neurological outcome in postanoxic patients after cardiac arrest: A prospective cohort study*

Objective: To evaluate the value of continuous electroencephalography in early prognostication in patients treated with hypothermia after cardiac arrest. Design: Prospective cohort study. Setting: Medical intensive care unit. Patients: Sixty patients admitted to the intensive care unit for therapeutic hypothermia after cardiac arrest. Intervention: None. Measurements and Main Results: In all patients, continuous electroencephalogram and daily somatosensory evoked potentials were recorded during the first 5 days of admission or until intensive care unit discharge. Neurological outcomes were based on each patient’s best achieved Cerebral Performance Category score within 6 months. Twenty-seven of 56 patients (48%) achieved good neurological outcome (Cerebral Performance Category score 1–2). At 12 hrs after resuscitation, 43% of the patients with good neurological outcome showed continuous, diffuse slow electroencephalogram rhythms, whereas this was never observed in patients with poor outcome. The sensitivity for predicting poor neurological outcome of low-voltage and isoelectric electroencephalogram patterns 24 hrs after resuscitation was 40% (95% confidence interval 19%–64%) with a 100% specificity (confidence interval 86%–100%), whereas the sensitivity and specificity of absent somatosensory evoked potential responses during the first 24 hrs were 24% (confidence interval 10%–44%) and 100% (confidence interval: 87%–100%), respectively. The negative predictive value for poor outcome of low-voltage and isoelectric electroencephalogram patterns was 68% (confidence interval 50%–81%) compared to 55% (confidence interval 40%–60%) for bilateral somatosensory evoked potential absence, both with a positive predictive value of 100% (confidence interval 63%–100% and 59%–100% respectively). Burst-suppression patterns after 24 hrs were also associated with poor neurological outcome, but not inevitably so. Conclusions: In patients treated with hypothermia, electroencephalogram monitoring during the first 24 hrs after resuscitation can contribute to the prediction of both good and poor neurological outcome. Continuous patterns within 12 hrs predicted good outcome. Isoelectric or low-voltage electroencephalograms after 24 hrs predicted poor outcome with a sensitivity almost two times larger than bilateral absent somatosensory evoked potential responses.

A novel approach for computer assisted EEG monitoring in the adult ICU

OBJECTIVE The implementation of a computer assisted system for real-time classification of the electroencephalogram (EEG) in critically ill patients. METHODS Eight quantitative features were extracted from the raw EEG and combined into a single classifier. The system was trained with 41 EEG recordings and subsequently evaluated using an additional 20 recordings. Through visual analysis, each recording was assigned to one of the following categories: normal, iso-electric, low voltage, burst suppression, slowing, and EEGs with generalized periodic discharges or seizure activity. RESULTS 36 (88%) recordings from the training set and 17 (85%) recordings from the test set were classified correctly. A user interface was developed to present both trend-curves and a diagnostic output in text form. Implementation in a dedicated EEG monitor allowed real-time analysis in the intensive care unit (ICU) during pilot measurements in four patients. CONCLUSIONS We present the first results from a computer assisted EEG interpretation system, based on a combination of eight quantitative features. Our system provided an initial, reasonably accurate interpretation by non-experts of the most common EEG patterns observed in neurological patients in the adult ICU. SIGNIFICANCE Computer assisted EEG monitoring may improve early detection of seizure activity and ischemia in critically ill patients.

P11.14 Postanoxic encephalopathy: the prognostic value of EEG monitoring

Introduction: The assessment of traumatic spinal cord injury (SCI) is actually mainly made on clinical bases. Many animal models of experimental SCI showed that motor evoked potentials (MEPs) and somatosensory evoked potentials (SEPs) are a sensitive measure of postinjury sensory and motor status. On the other hand, SEPs and MEPs have shown to be reliable in the assessment of the spinal cord functional integrity during spine and spinal cord surgeries. Objectives: To intraoperatively assess the spinal cord function in subjects during stabilization for spinal cord trauma, by recording muscular (mMEPs) and epidural motor evoked potentials (e-MEPs) along with cortical and epidural somatosensory evoked potentials (e-SEPs) in an effort to predict the outcome of the spinal cord injury. Methods: Intraoperative recording of m-MEPs and e-MEPs along with cortical SEPs and e-SEPs was attempted in 40 patients (19 with a complete SCI, and 12 uncompromised) during posterior stabilization for spine and spinal cord trauma. In order to test any kind of conductivity across the lesion site, in a subgroup of 6 subjects, all of them with a clinically complete SCI, the spinal cord has been stimulated cranially and caudally to the site of injury by the epidural electrodes in order to record responses from the scalp and the nerve. Results: All the uncompromised patients had normal recordings. The typical neurophysiologic pattern of complete SCI was the absence of both m-MEPs and e-MEPs caudally to the lesion site associated with a lack of cortical and e-SEPs cranially to the lesion site. In one patient with central cord syndrome the presence of D wave recorded from the caudal epidural electrode correctly predicted motor recovery. In the subgroup of 6 patients the intraoperative spinal cord stimulation positively add to the confirmation of the completeness of their lesion. Conclusion: Intraoperative neurophysiological evaluation of SCI patients can provide information about spinal cord function that is not retrievable by other clinical means and correctly predict the neurological outcome.