The Electroencephalogram in Metabolic/Toxic Coma

Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

The interpretation of the EEG in stupor and coma

This review discusses a variety of causes of stupor and coma and associated electroencephalographic (EEG) findings. These include metabolic disturbances such as hepatic or renal dysfunction, which are often characterized by slowing of background rhythms and triphasic waves. Hypoxia and drug intoxications can produce a number of abnormal EEG patterns such as burst suppression, alpha coma, and spindle coma. Structural lesions, either supra- or infratentorial, are reviewed. EEGs in the former may show focal disturbances such as delta and theta activity, epileptiform abnormalities, and attenuation of faster frequencies. In infratentorial lesions, the EEG may appear normal, particularly with a pontine lesion. Some patients may be encephalopathic because of ongoing epileptic activity with minimal or no motor movements. This entity, nonconvulsive status epilepticus (NCSE), is difficult to diagnose in obtunded/comatose patients, and an EEG is required to verify the diagnosis and to monitor treatment. Several EEG patterns and their interpretation in suspected cases of NCSE such as periodic lateralized epileptiform discharges (PLEDs), bilateral independent periodic lateralized epileptiform discharges (BIPLEDs), generalized periodic epileptiform discharges (GPEDs), and triphasic waves are reviewed. Other entities discussed include the locked-in syndrome, neocortical death, persistent vegetative state, brainstem death, and brain death.

The EEG in coma

The EEG allows insight into thalamocortical function in comatose patients when this is inaccessible clinically. A single EEG can help with broad diagnostic categorization whereas continuous or serial EEG provides monitoring for unstable and potentially treatable conditions and for monitoring the effects of therapy. The EEG plays a supplemental role in establishing the prognosis in disease states that are capable of causing neuronal death. The most prevalent and problematic of these conditions involves survivors of cardiac arrest who are initially in coma with intact brainstem reflexes. In such patients single EEGs are of 100% specificity for no possibility of recovery of consciousness only for essentially complete generalized suppression (<10 microV) after the first day of the arrest. Several other generalized patterns, including less marked suppression, burst-suppression, epileptiform activity, periodic complexes, and alpha-theta coma patterns, usually but not invariably indicate a poor outcome. Serial EEGs, continuous raw and automated "trending," testing of reactivity, and the inclusion of multiple variables hold promise for an improved role in the prognostic determination in these patients.

Metabolic and inflammatory cerebral diseases: electrophysiological aspects

The electroencephalogram (EEG) is an important diagnostic tool in coma. Although comatose patients may be similar on neurological examination, the EEG reveals a wide range of abnormalities. For metabolic and septic encephalopathies, the "anesthesia model" is a useful analogy. The EEG is very sensitive to the depth or severity of brain dysfunction in coma as well as the direction of the process if serial tracings or continuous recordings are used. While the EEG is rarely specific for the etiology of coma, it may help determine the class or general category of disease process. In conditions capable of causing neuronal death, e.g., anoxia-ischemia, the EEG can be of prognostic value.

"Periodic" seizures

PURPOSE

To describe regularly recurring ictal phenomena as recorded in a single patient whose seizure disorder related to a left temporal cavernous angioma.

METHODS

Seizures were recorded by left temporal subdural strip electrodes which were bilaterally placed because of ambiguous seizure origin and right temporal memory dysfunction at Wada testing. Seizure length, interseizure intervals, and interseizure onset intervals were visually assessed. The coefficient of variation was used as an estimate of variability in seizure periodicity.

RESULTS

Mean seizure durations varied from 68 to 95 s; coefficients of variation varied from 0.08 to 0.18, values similar to other periodic biological phenomena. Mean daily seizure intervals varied from 96 to 152 s with coefficients of variation ranging from 0.12 to 0.35. Interseizure onset intervals had smaller coefficients of variation (0.03-0.20). Manifestations of these simple partial seizures included a rising epigastric sensation and nausea.

CONCLUSIONS

Previously described periodic EEG phenomena are interictal events or appear with peripheral events of similar cadence. Therefore, we remain unaware of any documentation of periodic ictal electrographic events. The restricted propagation and duration of these recorded seizures may have simplified their pathophysiology allowing a stereotyped involvement of excitatory and inhibitory mechanisms producing the periodicity.

An electroencephalographic classification for coma

BACKGROUND

The assessment of thalamocortical function in comatose patients in the intensive care unit (ICU) can be difficult to determine. Since the electroencephalogram (EEG) affords such assessment, we have developed an EEG classification for comatose patients in our general ICU.

METHODS

One hundred EEGs were classified in a blinded fashion by two EEGers, using our method and that of Synek. Interobserver agreement was assessed using kappa score determination.

RESULTS

Kappa scores were 0.90 for our system and 0.75 for the Synek system. (The Kappa score represents the inter-rater agreement that is beyond chance; 0.90 is almost perfect agreement, while 0.75 is substantial agreement).

CONCLUSION

Our system for classifying EEGs in comatose patients has a higher interobserver reliability than one that was previously published. This EEG classification scheme should be useful in clinical electrophysiological research involving ICU patients, allowing for internal consistency and comparisons among centres.