Epilepsy Nervous System Diseases
Conditions
Interventions
Patient selection:
The researchers will retrospectively identify 104 EEG tracings from the MNI EEG hospital database, from consecutive patients between 20/10/2022 and 20/10/2016. This time frame coinc
Sponsors
McGill University
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: 1. Patients =15 years of age whose EEG classify as either normal, focal epileptiform, generalized epileptiform, focal non-epileptiform, or diffuse non-epileptiform
Exclusion criteria
Exclusion criteria: 1. Patients <15 years of age 2. Dual pathology 3. Absence of sufficient clinical information to grade in 1 of the 5 categories such as the absence of recorded seizures during the stay in the epilepsy monitoring unit or insufficient information on etiology of non-epileptiform EEG anomalies from the medical chart
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the SCORE-AI algorithm in classifying the five main EEG categories will be compared to that of human experts. These variables will be assessed after all retrospective data have been extracted. | — |
Secondary
| Measure | Time frame |
|---|---|
| 1. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the SCORE-AI algorithm when used on long-term (20-hour) recordings will be assessed after all retrospective data have been extracted. 2. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the new SCORE-AI feature (posterior dominant rhythm) will be assessed in 25-minute routine EEG recordings. These variables will be assessed after all retrospective data have been extracted. | — |
Countries
Canada, Denmark, Norway
Contacts
Public ContactBirgit Frauscher
Outcome results
None listed