Paroxysmal slow wave events predict epilepsy following a first seizure

Abstract

Objective: Management of a patient presenting with a first seizure depends on the risk of additional seizures. In clinical practice, the recurrence risk is estimated by the treating physician using the neurological examination, brain imaging, a thorough history for risk factors, and routine scalp electroencephalogram (EEG) to detect abnormal epileptiform activity. The decision to use antiseizure medication can be challenging when objective findings are missing.There is a need for new biomarkers to better diagnose epilepsy following a first seizure. Recently, an EEG-based novel analytical method was reported to detect paroxysmal slowing in the cortical network of patients with epilepsy. The aim of our study is to test this method's sensitivity and specificity to predict epilepsy following a first seizure. Methods:We analyzed interictal EEGs of 70 patients admitted to the emergency department of a tertiary referral center after a first seizure. Clinical data from a follow-up period of at least 18 months were available. EEGs of 30 healthy controls were also analyzed and included. For each EEG, we applied an automated algorithm to detect paroxysmal slow wave events (PSWEs). Results:Of patients presenting with a first seizure, 40% had at least one additional recurring seizure and were diagnosed with epilepsy. Sixty percent did not report additional seizures. A significantly higher occurrence of PSWEs was detected in the first interictal EEG test of those patients who were eventually diagnosed with epilepsy. Conducting the EEG test within 72 h after the first seizure significantly increased the likelihood of detecting PSWEs and the predictive value for epilepsy up to 82%. Significance:The quantification of PSWEs by an automated algorithm can predict epilepsy and help the neurologist in evaluating a patient with a first seizure.

Paroxysmal Slow-Wave Events Are Uncommon in Parkinson’s Disease

“…When searching for the presence of PSWEs, consistent with previous studies we found that epilepsy patients have significantly more PSWEs compared with healthy controls ( Figure 3 ) [ 11 , 13 ]. Unlike our hypothesis, the temporal characteristics of EEG slowing in PD patients did not show a significant difference in the number of PSWEs compared with control ( Figure 3 ).…”

“…However, reduced spontaneous eye movement as a manifestation of hypomimia, a common PD symptom, may contribute to this observation. Additionally, similar trends regarding frontal PSWE in epilepsy patients were found in a previous study [ 13 ].…”

“…The definition of PSWEs in humans (a decrease in MPF to below 6 Hz for more than 5 consecutive seconds) was made using analysis of EEG recordings from AD patients and control subjects [ 11 ]. These thresholds were found to be valid also in epilepsy patients [ 11 , 13 ]. In this study, we tested, for the first time, EEG recordings of PD patients.…”

“…Recently, a new approach has emerged in the study of EEG slowing in other neurological disorders, postulating that cortical slowing is composed of transient paroxysmal slowing of the cortical network [ 11 , 12 ]. These paroxysmal slow-wave events (PSWEs) are transient low-frequency episodes defined by a median power frequency (MPF) below 6 Hz for at least 5 consecutive seconds in humans and an MPF below 5 Hz for 10 s or more in rodents ( Supplementary Figure S1 ) [ 11 , 13 ]. Investigations of EEG recordings from AD and epilepsy patients revealed that network slowing in these pathologies is discrete and composed of PSWEs.…”

“…Investigations of EEG recordings from AD and epilepsy patients revealed that network slowing in these pathologies is discrete and composed of PSWEs. Further research found significant potential in the quantification of PSWEs to serve as diagnostic, predictive, and pharmacodynamic biomarkers in AD and epilepsy [ 11 , 12 , 13 ]. However, this new approach of PSWE quantification to evaluate cortical slowing has not been tested in patients with PD.…”