Health Condition 1: G409- Epilepsy, unspecified Health Condition 2: F99- Mental disorder, not otherwise specified Health Condition 3: I669- Occlusion and stenosis of unspecified cerebral artery Health Condition 4: I95-I99- Other and unspecified disorders of the circulatory system
Conditions
Interventions
None listed
Sponsors
Indian Council of Medical Research
Eligibility
Inclusion criteria
Inclusion criteria: 1. Age >= 12 years and 2. Patients with epilepsy: a. Patients with confirmed diagnosis of epilepsy according to ILAE guidelines (whether on AEDs or not). b. If the patient is on AEDs at the time of EEG recording, at least one seizure should have occurred in the 180-day period preceding the EEG recording and there should have been no change in the AED regimen post the last seizure date. c. One of the following: (i) Normal MRI Brain / CT Brain (ii) A single focal lesion or gliosis in one region in MRI Brain / CT Brain with size single cavernoma, AVM, small tumor, small infarct, small intracranial haemorrhage). 3. Patients with epilepsy mimickers: Patients with epilepsy mimickers having abnormal confirmed findings for etiology in corresponding diagnostic tests. 4. Healthy subjects: No history of unconsciousness, neurological, psychiatric or developmental disorders. 5. EEG of patient recorded on Natus Brain Monitor EEG Machine (in order to maintain uniformity in data acquisition).
Exclusion criteria
Exclusion criteria: 1. MRI Brain / CT Brain findings showing extensive damage to brain >= 20mm as they would likely alter biomarkers. This includes disorders like TBI, stroke, encephalitis, meningoencephalitis, multiple NCC, multiple tuberculomas. 2. History of intracranial bleeding (e.g., subarachnoid, intraparenchymal). 3. Patients with epilepsy mimickers not having confirmed etiology. 4. Patients having dementia, Parkinsons disease and other neurodegenerative disorders, neurodevelopmental disorders, cerebral palsy, hypoxic ischemic encephalopathy. 5. Patients with confounding psychiatric disorders like schizophrenia and bipolar mood disorder. 6. Patients with a history of drug abuse or alcohol addiction. 7. Patients having provoked seizures (E.g. seizure within 1 week of any brain insult such as head injury/stroke/brain infection, hyponatremia, hypocalcemia, hypomagnesemia, hyperammonemia, hypoglycemia, drug toxicity). 8. Seizures only during pregnancy. 9. Non-availability of a 5-minute eyes-closed awake resting state portion (see Quality Assurance Measures) or excessive artifacts in the EEG recording rendering it unusable for analysis. 10. Patients not providing informed consent
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Development of Machine Learning and Deep Learning based models for Epilepsy Diagnosis. Assessment of model performance using a validation dataset (Primary Metric: Area Under ROC)Timepoint: 3 years | — |
Secondary
| Measure | Time frame |
|---|---|
| Exploratory analyses for group differences between epileptic patients and controls.Timepoint: First 2 years | — |
Countries
India
Contacts
Public ContactSiddharth Panwar
IIT Delhi
Outcome results
None listed