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Active, Not Recruiting

NCT Number: NCT06922734

Epilepsy Watch After Vascular Events: Frequency, Outcomes, and Risk Markers

This research aims to determine the frequency of seizures in patients following a stroke, identify risk factors associated with post-stroke seizures, and characterize EEG changes linked to these seizures. Unexplored alterations in the aperiodic component of the EEG in post-stroke patients could potentially serve as novel biological markers for epilepsy after stroke.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

About this study

This study included patients with stroke or post-stroke seizures who were admitted to the Neurology Division at the University Medical Centre Maribor, Slovenia, over a 12-month period. The anticipated number of patients was approximately 600-650. Inclusion criteria encompassed acute stroke or seizure occurring at any point after the stroke. Stroke classification was based on the World Health Organization (WHO) criteria, while post-stroke seizures and epilepsy were defined according to the International League Against Epilepsy (ILAE) definitions and classifications.

All participants provided written informed consent after being thoroughly informed about the study. The study was pre-approved by the Medical Ethics Committee of the Republic of Slovenia (Approval No. 48/08/14 and Approval No. 0120-302/2024-2711-3). Patients who did not meet the inclusion criteria or could not undergo diagnostic procedures as outlined in the research protocol were excluded based on principles of good clinical practice.

During the 12-month study period, demographic, imaging, laboratory, and neurophysiological data were prospectively collected from all hospitalized stroke patients.

Data Collection

Patient history was utilized to gather information on neurological impairments, seizure onset, and risk factors for cerebrovascular diseases. For patients who experienced seizures, the interval between stroke onset and seizure occurrence (in days) was calculated to distinguish early from late post-stroke seizures.

Vital signs, including blood pressure, pulse, height, weight, and body mass index (BMI), were recorded. Neurological impairment was assessed on admission and discharge through clinical examinations and standardized scales, including the National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin Scale (mRS).

Laboratory and Diagnostic Assessments

Within 24 hours of admission, blood samples were collected to measure urea, creatinine, electrolytes, uric acid, cholesterol, triglycerides, liver enzymes, blood glucose, cystatin C, high-sensitivity C-reactive protein (hsCRP), red blood cell count, hemoglobin concentration, and urine analysis.

Within 72 hours of admission, imaging diagnostics (computed tomography [CT] or magnetic resonance imaging [MRI] of the brain) and functional diagnostics (electroencephalography [EEG]) were performed. The study population consisted of patients with ischemic stroke, hemorrhagic stroke, subarachnoid hemorrhage, and other rare cerebrovascular diseases (CVD).

Patient Grouping

Clinical Seizure Data and Timing of Onset Post-Stroke:

Patients were classified into three groups:

No seizures after stroke ("no EPI")

Early seizures (within 7 days post-stroke; "early EPI")

Late seizures (more than 7 days post-stroke; "late EPI")

EEG-Based Grouping:

Patients were additionally grouped based on EEG results:

EEG+/EPI+: Epileptiform EEG changes with seizures

EEG+/EPI-: Epileptiform EEG changes without seizures

EEG-/EPI-: No epileptiform EEG changes and no seizures

KON: Control group of healthy individuals

Planned Analyses

Demographic Analysis:

Data on gender, age, cerebrovascular risk factors, stroke type, functional impairment (assessed by NIHSS and mRS), seizure prevalence, and EEG changes were analyzed for all participants. Subgroup demographic analyses were performed based on clinical and EEG data.

EEG Analysis:

Standard visual EEG analysis included the evaluation of spectral frequency bands and the identification of focal or generalized epileptiform abnormalities. Preprocessing involved removing segments with noise, saturation, or absence of EEG activity. Ocular artifacts, including blink-related components, were identified using independent component analysis, and the EEG signals were reconstructed without these artifacts.

Using spectral parameterization (SPECPARAM 2.0 in Python), power spectral density was calculated for each patient. Aperiodic components were analyzed by extracting the exponent and offset from each frequency spectrum. Welch's t-tests were used to compare these parameters between groups. Additionally, standardized low-resolution brain electromagnetic tomography (sLORETA) was employed for signal source localization, micro-EEG potential analysis, and network distribution assessment.

Statistical Data Analysis

Descriptive Statistics:

Basic descriptive metrics, including mean, standard deviation, median, minimum, maximum, and quartiles, were calculated for each variable to assess within-group distributions. Frequencies and relative frequencies were determined for categorical variables, with emphasis on the prevalence rates within the "no EPI," "early EPI," and "late EPI" groups. Results were presented in frequency tables.

Inferential Statistics:

Parametric tests (for normally distributed data):

Two-group comparisons: t-tests

Multi-group comparisons: ANOVA

Non-parametric tests (for non-normally distributed data):

Two-group comparisons: Mann-Whitney U tests

Multi-group comparisons: Kruskal-Wallis tests

For EEG-based groups, extracted offset and exponent values of aperiodic components were compared using Welch's t-tests. Correlation analyses (Pearson's or Spearman's) were performed based on data distribution. Post-hoc analyses used Dunn's tests for pairwise comparisons when significant differences were identified.

Categorical Data Analysis:

Chi-square tests evaluated differences between categorical variables among patient groups. Fisher's exact test was applied when expected frequencies were too low for the chi-square test.

Survival Analysis:

To examine seizure onset timing, survival analysis was conducted using the time from stroke onset as the time variable. Kaplan-Meier analysis estimated survival curves representing seizure-free intervals, and log-rank (Mantel-Cox) tests were used to compare survival distributions across groups. This analysis helped to identify factors associated with seizure onset timing among stroke patients.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients were eligible for inclusion if they had experienced an acute stroke or a seizure occurring at any point after a previous stroke.

Exclusion criteria

Patients were excluded from the study if they did not meet the inclusion criteria or if diagnostic procedures could not be performed in accordance with the research protocol. Exclusions were made following good clinical practice principles.

Treatment and study plan

Primary outcomes

  1. Post-stroke seizure prevalence

    Time frame: From enrollment of first patient to the last one in 12 months

  2. Risk factors of post-stroke seizures

    Time frame: From enrollment of first patient to the last one in 12 months

    Investigators are interested in serum and radiological biomarkers as risk factors for post-stroke seizures

  3. post-stroke EEG characteristics

    Time frame: From enrollment of first patient to the last one in 12 months

    Investigators are interested in specific EEG changes which may indicate risk factors for post-stroke seizures

Secondary outcomes

  1. Aperiodic EEG component in patients after stroke with and without seizures

    Time frame: From enrollment to the end of hospitalisation

    The parameters of the aperiodic EEG component in patients with epileptic seizures or epileptiform graphoelements in the EEG differ from patients without seizures or without epileptiform graphoelements and from the control group of healthy subjects.

Sponsors and collaborators

Lead sponsor

University Medical Centre Maribor

Other

Collaborators

  • IRCCS San Camillo, Venezia, Italy

Registry information

Official study title

Post-stroke Seizures and EEG Analysis

Acronym: EY-WAVEFORMS

Important dates

Study start
2014
Primary completion
2015
Study completion
2026
First posted
Apr 10, 2025
Registry last updated
Feb 5, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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