Epilepsy Watch After Vascular Events: Frequency, Outcomes, and Risk Markers
NCT ID: NCT06922734
Last Updated: 2026-02-05
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
ACTIVE_NOT_RECRUITING
602 participants
OBSERVATIONAL
2014-11-01
2026-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Predisposing Factors for Post-stroke Epilepsy
NCT05864547
Continuous Video- EEG Monitoring in the Acute Phase in Patients With a Cerebrovascular Attack- Randomisation of a Subpopulation Regarding Treatment Strategy
NCT01862952
Post Stroke Epileptic Seizures Risk Forecast
NCT03848273
" Virtual Brain "-Based Interpretation of Electrophysiological Signals in Epilepsy
NCT02603640
Assessment of Severity and Prognosis for Patients With Status Epileptics(SE)
NCT02269137
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
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.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
EEG+/EPI+ group
Patients with epileptiform EEG changes and seizures
No interventions assigned to this group
EEG+/EPI- group
Patients with epileptiform EEG changes but no seizures
No interventions assigned to this group
EEG-/EPI-group
Patients without epileptiform EEG changes and no seizures
No interventions assigned to this group
KON group
A control group of comparable healthy individuals
No interventions assigned to this group
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
18 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
IRCCS San Camillo, Venezia, Italy
OTHER
University Medical Centre Maribor
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Albin Gačnik MD
MD, Senior Consultant Neurologist
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Martin Rakusa, Asoc. Prof.
Role: STUDY_CHAIR
UKC Maribor
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
UKC Maribor
Maribor, , Slovenia
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
Bentes C, Rodrigues FB, Sousa D, Duarte GS, Franco AC, Marques R, Nzwalo H, Peralta AR, Ferro JM, Costa J. Frequency of post-stroke electroencephalographic epileptiform activity - a systematic review and meta-analysis of observational studies. Eur Stroke J. 2017 Dec;2(4):361-368. doi: 10.1177/2396987317731004. Epub 2017 Sep 13.
Tatillo C, Legros B, Depondt C, Rikir E, Naeije G, Jodaitis L, Ligot N, Gaspard N. Prognostic value of early electrographic biomarkers of epileptogenesis in high-risk ischaemic stroke patients. Eur J Neurol. 2024 Jan;31(1):e16074. doi: 10.1111/ene.16074. Epub 2023 Sep 27.
Tanaka T, Ihara M, Fukuma K, Mishra NK, Koepp MJ, Guekht A, Ikeda A. Pathophysiology, Diagnosis, Prognosis, and Prevention of Poststroke Epilepsy: Clinical and Research Implications. Neurology. 2024 Jun 11;102(11):e209450. doi: 10.1212/WNL.0000000000209450. Epub 2024 May 17.
Pani SM, Saba L, Fraschini M. Clinical applications of EEG power spectra aperiodic component analysis: A mini-review. Clin Neurophysiol. 2022 Nov;143:1-13. doi: 10.1016/j.clinph.2022.08.010. Epub 2022 Aug 28.
Fukuma K, Tojima M, Tanaka T, Kobayashi K, Kajikawa S, Shimotake A, Kamogawa N, Ikeda S, Ishiyama H, Abe S, Morita Y, Nakaoku Y, Ogata S, Nishimura K, Koga M, Toyoda K, Matsumoto R, Takahashi R, Ikeda A, Ihara M. Periodic discharges plus fast activity on electroencephalogram predict worse outcomes in poststroke epilepsy. Epilepsia. 2023 Dec;64(12):3279-3293. doi: 10.1111/epi.17760. Epub 2023 Oct 30.
Related Links
Access external resources that provide additional context or updates about the study.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
KME št. 0120-302/2024-2711-3
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.