Epilepsy Clinical Trial
— CIEDOfficial title:
Clinical Validation of Criteria for Identification of Epileptiform Electroencephalography Discharges in Sensor Space and Source Space
NCT number | NCT03533374 |
Other study ID # | CIED |
Secondary ID | |
Status | Completed |
Phase | |
First received | |
Last updated | |
Start date | January 1, 2012 |
Est. completion date | January 1, 2018 |
Verified date | July 2019 |
Source | Aarhus University Hospital |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
Electroencephalography (EEG) records electric activity of the brain using electrodes placed
on the scalp. EEG is an important tool in the diagnostic work-up of patients with epilepsy.
Specific types of sharp EEG discharges (epileptiform discharges) are associated with patients
with epilepsy.
The International Federation of Clinical Neurophysiology (IFCN) has recently published a set
of six operational criteria for identifying epileptiform discharges. At least four criteria
need to be present in order to classify a discharge as epileptiform. These criteria are
largely based on expert opinion and have not been validated yet. It is not clear what the
sensitivity and specificity of these criteria are, and which combination of these criteria
are optimal. Each criterion is based on visual assessment. However, it is not known what the
inter-rater agreement of these criteria are.
EEG is traditionally inspected in sensor space, i.e. in the recording channels. Advances in
signal analysis made possible reconstructing the electric currents in the regions of the
brain generating them, and displaying the signals in the source space, instead of the sensor
space.
The objectives of this study are: to determine the inter-rater agreement of the IFCN criteria
by visual analysis in sensor space, to determine the combination of criteria with the best
accuracy (sensitivity and specificity) and assess the accuracy of evaluating the discharges
in source space.
The raters will analyze EEG recordings from 100 patients, from two groups: consecutive
patients with epilepsy and consecutive patients with non-epileptic paroxysmal episodes. EEG
was recorded during long-term video-EEG monitoring. As reference standard, the investigators
used the evaluation of the patients´ habitual clinical episode. The performance of the
criteria in sensor-space and the analysis in source space will be compared with the
unrestricted expert scorings.
Status | Completed |
Enrollment | 100 |
Est. completion date | January 1, 2018 |
Est. primary completion date | January 1, 2018 |
Accepts healthy volunteers | No |
Gender | All |
Age group | N/A and older |
Eligibility |
Inclusion Criteria: 1. Patients who underwent long-term video-EEG monitoring 2. Patients who had at least one habitual episode (seizure) recorded on video and EEG. 3. Patients with sharp transients. 4. For patients with epilepsy: the interictal (epileptiform) sharp transients are concordant with the ictal recording Exclusion Criteria: Patients with both epileptic seizures and non-epileptic seizures (paroxysmal episodes). |
Country | Name | City | State |
---|---|---|---|
n/a |
Lead Sponsor | Collaborator |
---|---|
Sándor Beniczky | Aarhus University Hospital, Central Denmark Region, Danish Epilepsy Centre, Dianalund, Denmark, Oslo University Hospital, University Health Network, Toronto, University Hospital Erlangen |
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Inter-rater Agreement of the International Federation of Clinical Neurophysiology (IFCN) Criteria (Cut-off=4) in Sensor Space and of Detection of Epileptiform Discharges (EDs) in Source Space | Inter-rater agreement of IFCN criteria (cut-off=4) in sensor space and of detection of EDs in source space was calculated using Gwet´s Agreemen Coefficient (AC1). We calculated Gwet's coefficients of agreement AC1 for beyond chance agreement, because, compared with Cohen's Kappa, the Gwet's agreement coefficient is less affected by prevalence and marginal probability and thereby avoids the problem known as the "paradoxes of kappa". Strength of agreement beyond chance was interpreted according to Landis and Koch criteria: poor (<0), slight (0·01-0·20), fair (0·21-0·40), moderate (0·41-0·60), substantial (0·61-0·80), and almost perfect (0·81-1·00). |
1 year | |
Primary | Sensitivity and Specificity IFCN Criteria (Cut-off=4) | This is a diagnostic study, hence sensitivity and specificity must be calculated from different groups: sensitivity form the group of patients with epilepsy and specificity from the gruoup of patients who do not have epilepsy. Sensitivity: the percentage of patients with abnormal index test (true positives) among patients with epilepsy. Specificity: the percentage of patients with normal index test (true negatives) among patients who do not have epilepsy. |
1 year | |
Primary | The Sensitivity and Specificity of Detecting EDs in Source-space | This is a diagnostic study, hence sensitivity and specificity must be calculated from different groups: sensitivity form the group of patients with epilepsy and specificity from the group of patients who do not have epilepsy. Sensitivity: the percentage of patients with abnormal index test (true positives) among patients with epilepsy. Specificity: the percentage of patients with normal index test (true negatives) among patients who do not have epilepsy. |
1 year |
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