[Status epilepticus after brain tumor surgery]

ABTRACT

BACKGROUND

Status epilepticus (SE) is characterized by continuous course of clinical and/or electrographic epileptic seizures. There are little data on the course and outcomes of SE after resection of brain tumors.

OBJECTIVE

To analyze clinical and electrographic manifestations of SE, its course and outcomes in short-term period after resection of brain tumors.

MATERIAL AND METHODS

We analyzed medical records of 18 patients over 18 years old between 2012 and 2019. All patients underwent resection of brain tumor and developed SE after surgery. Clinical criteria were repeated epileptic seizures without interictal recovery of consciousness, stereotypical motor phenomena, impaired consciousness with continued epileptic activity according to video-EEG data. We analyzed EEG data, neurological status, CT and laboratory data.

RESULTS

Metastases (33%) and meningiomas (16%) prevailed. Supratentorial tumors were observed in 61% of patients. Two patients had preoperative seizures. Non-convulsive SE was diagnosed in 62% of patients. SE was successfully treated in 77% of cases. Mortality rate in patients with SE was 44%.

CONCLUSION

Early postoperative SE is rare after brain tumor surgery (about 0.09%). Nevertheless, this complication is associated with high mortality. Non-convulsive SE is common (62%) that should be considered in postoperative management.

[Long-term EEG monitoring in patients with acute traumatic brain injury]

OBJECTIVE

To investigate the informativeness of long-term scalp EEG monitoring in patients with acute traumatic brain injury (TBI).

MATERIAL AND METHODS

The informativity of long-term EEG monitoring (LTM) was performed in 60 patients with acute severe TBI. Odd ratios (OR) of unfavorable outcome and non-convulsive status epilepticus (NCSE) among clinical, neurophysiological and radiological features were calculated.

RESULTS

EEG features of the unfavorable outcome are: slowing of the dominant background rhythm below q range (OR 3.5, CI 1.2-10.7), absence of frontal-occipital gradient (OR 10.2, CI 1.89-10.12), absence of reactivity (OR 8.75, CI 2.14-35.7), absence of variability (OR 6.25, CI 1.72-22.6) and absence of NREM sleep, stage 2 (OR 5.8, CI 1.79-18.91). Clinical features associated with the unfavorable outcome are: a decrease in GCS score (OR 1.25, CI 1.07-1.47), TBI severity (OR 2.46, CI 1.16-5.18), axial dislocation (OR 4.45, CI 1.08-18.29). ORs for NCSE are significant for the following EEG features: presence of rhythmic and periodic patterns (RPP) (OR 11.92, CI 1.37-103.39), stimulus induced RPP (OR 23.14, CI 2.56-209.34), "plus" modifier (OR 4.11, CI 1.13-14.91) and electrographic evolution (OR 13.05, CI 3.59-47.39). Background rhythm slowing below q range reduces NCSE probability (OR 3.33, CI 1.09-10).

CONCLUSION

Long-term EEG monitoring is an informative tool for prognosis of outcome and diagnosis of NCSE in patients with severe TBI. The risk of NCSE increases with Marshall score but NCSE is not associated with poor outcome that requires an individual selection of intensive care.

[Electroencephalography in acute stroke]

OBJECTIVE

To determine the incidence of non-convulsive status epilepticus, epileptiform activity, rhythmic and periodic patterns in patients with acute stroke.

MATERIAL AND METHOD

An analysis of electroencephalography (EEG) in 86 stroke patients in the neurointensive care unit of the tertiary medical center was performed. Criteria for starting EEG recording were epileptic seizures or clinical suspicion of uncontrolled epileptic status. The ictal-interictal continuum biomarkers and the diagnostic value of EEG for prediction of survival and recovery were assessed.

RESULTS

Pathological changes on EEG were recorded in 84% of patients. These patients showed the absence of the dominant occipital rhythm (66%) and hemispheric slowing (42%). Diffuse slowing below the theta range was observed in 41% of patients. EEG reactivity was absent in 20%. Sporadic epileptiform discharges were recorded in 36% of patients and rhythmic and periodic patterns in 26%. Reliable predictors of the unfavorable outcome were the absence of dominant occipital rhythm, lack of reactivity, and low amplitude of the background EEG. No association between the recording of epileptiform activity and the probability of death was shown.

CONCLUSION

The most useful EEG biomarkers for predicting survival are amplitude, dominant frequency of background EEG activity and reactivity to external stimulus. Sporadic epileptiform discharges, rhythmic, and periodic patterns are not mandatory associated with a negative prognosis in stroke patients.