Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT05140265 |
| Other study ID # |
21-351 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
October 11, 2021 |
| Est. completion date |
December 31, 2030 |
Study information
| Verified date |
June 2024 |
| Source |
University of New Mexico |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
This proposal outlines the steps required for the creation of a pilot database of EEG
recordings and de-identified medical records from patients internally referred within the
UNMH Comprehensive Epilepsy Center. The UNMH EEG Corpus would be the first database of its
kind. Other public databases contain either patient EEG signals or medical records, but
without both kinds of information, it is impossible to relate pre-treatment neurobiomarkers
with post-treatment prognosis. The database will also contain information that can improve
seizure localization based off of scalp and intracranial EEG, and the requisite data for the
creation of algorithms that forecast seizure activity; a development that could ultimately
lead to novel responsive neural stimulation procedures that suppress seizures before they
begin.
Description:
Retrospective De-identified EEG and Clinical Database Creation:
The proposed database (UNMH EEG corpus) will be created in stages and designed to increase in
complexity and functionality given future funding and tool development. The initial scope for
this project includes the construction of a relational database that links patient
demographic data (medical records, EEG study number, date of birth) which will be linked to
the study number. This list will be kept for 6 years from the completion of study and will be
stored in locked office cabinet as a paper form (source documentation) and password protected
computer in locked office (electronic version). Then, the rest of the data collection will
include algorithmically de-identified clinical reports (e.g. progress notes), recording
meta-data (e.g. montage configuration), and de-identified clinical EEG with only study number
without PHI. Future work beyond the scope of this pilot project will involve: annotating the
EEG trace with the timing and type of seizure (or artifact), extracting medication history
from the patient records, standardizing notes on treatment history and outcome, review that
ePHI has been removed, and dissemination. A full patient assessment can also include MRI, MEG
and PET scans and a final database should also include these valuable images. The creation of
the pilot UNMH EEG corpus will focus on the subset of patients internally referred within
UNMH for whom an EEG was performed, a treatment was provided, and a follow up assessment
occurred. This inclusion criteria will guarantee that the minimum data is present to
statistically relate pre-treatment EEG with post-treatment prognosis.
Collection of De-identified Data Retrospectively:
Time Frame: 1) from current up to August 8, 2007 when Nihon Kodhen Neuroworkbench was started
at UNM, 2) From the start of study, each year, the investigator will add previous year's
de-identified data to the database until the last dataset of 2027. For example, in January to
February 2023, the investigator will add 2022 data to the database. The investigator will add
previous year's data to the database until 2028 with the last dataset till 2027.
The investigator will generate randomized de-identified study number by computer programing.
The investigator will create the secure table of de-identified study number to link patient's
PHI (medical record number, EEG study number, Date of Birth). This table will be stored in
the locked cabinet in PIs' office. Also, the electronic version will be stored in HSC
password protected computer under HSC IT secured drive with only access by PIs and study
coordinator.
Once the study number is generated, all the de-identified data will be stored under the study
number so that no PHI is present in any of research data.
The investigator will only extract the data from the patients who are 18 years or older at
the time of EEG obtained. The investigator will exclude any vulnerable groups or information.
Please see below for inclusion and exclusion criteria. Children under age of 18 years old
will be excluded. Since, there is no informed consent or direct interaction with the patient
in this retrospective data analysis, the patient of any particular ethnic/ racial/ primary
language will not be screened nor targeted. Also, there will be no particular exclusion for
Spanish speaking patients for the above reason.
The investigator will all de-identify EEG data from the clinical EEG database (i.e.
Neuroworkbench of Nihon Kodhen EEG system) and import these to password protected secure
study server in PI's HSC IT secured drive domain. There will be no video data of EEG since
video of patient can be easily identify the patient's information.
Clinical Information: each patient's Neurology notes (History and Physical, Neurology
Progress Note, Neurology Consultation Note, Neurology Clinic note, Neurology Discharge
Summary, Neurodiagnostic Report of EEG results, Neuroimaging studies (brain MRI, brain PET,
brain MEG), and Patient's Medication List of Anti-seizure medication (ASM) will be pulled.
These clinical documentations will be de-identified (removing all PHI) and linked to the
study number. After the de-identification and link to study number, the clinical information
will be stored in password protected secure study server with de-identified EEG data. While
the investigators are creating automated de-identification method, the investigators will
manually extract the data and manually de-identify them. Once the automated process is
established, the investigators will also perform quality check with manual and automated
process comparison.
Specifically, all data (the EEG-BIDS files, the SQL database, and the Excel sheet) will be
stored on an internal hard drive within a UNM HSC IT managed desktop PC, physically located
in Dr. Sam McKenzie's office in Rm 209A in RGFH. The PC is on the UNM HSC network and the
computer runs the UNM HSC mirror of Windows 10. The room is always locked and the PC requires
password log in.
The investigators will use the EEG-BIDS file format to store all data and organize the
database. This file format specifies a path structure tree with particular nomenclature
(Figure 1). Each patient is assigned a directory containing subdirectories for each session
and data modality. For non-identifying details about the patient demographics and recording
details, information will be saved in two file types: a *.tsv file for data values and a
*.json file for descriptive metadata. EEG files with de-identification will be downsampled to
250 Hz, for hard drive storage efficacy, and saved into the European Data Format. Also
accompanying the EDF EEG file will be a 'coordinates' file which specifies the location of
anatomical landmarks used for montage placement. Another 'events' file will contain
annotations of events observed by clinicians in the EEG. This data will be imported from the
original Nihon Kohden annotated dataset using the Python MNE toolbox1.
Within this file structure we will also save text files with de-identified clinical notes
imported from Cerner Millennium detailing medication, diagnosis, treatment, and prognosis.
Non-identifying patient data will additionally be stored in a SQL database with a randomized
patient identifier.
An Excel sheet will store random patient identification number (used in the EEG-BIDS file and
in the SQL database) and the corresponding patient identifying number for subsequent
re-identification if needed.
