Integrating eSAGE With EHR Data Using Machine Learning for the Early Detection and Monitoring of Cognitive Impairment in Individuals
Integrating the Electronic Self-administered Gerocognitive Examination (eSAGE) With Electronic Health Records (EHR) Data Using Machine Learning (ML) for the Early Detection and Monitoring of Cognitive Impairment in Individuals
Study Overview
Status
Intervention / Treatment
Detailed Description
This is a retrospective and prospective record review trial for patients who are followed at the Center for Cognitive and Memory Disorders.
eSAGE assessment data (including cognitive data, behavioral data, timing data and other metadata) as well as varying amount of electronic health records (EHR) data will be collected on all eligible subjects. Machine learning techniques with feature selection will identify important EHR variables to determine what may be useful for the prediction of cognitive impairment.
Based on the EHR analysis additional questions will be added to the eSAGE to make an enhanced eSAGE version (eSAGE+). The goal of the eSAGE+ is to facilitate the identification of cognition impairment, and ultimately have a translational impact on Alzheimer's disease (AD) identification and management.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
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Ohio
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Columbus, Ohio, United States, 43123
- Nicole Vrettos
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- 1. Males and females 50 years of age and over who complete the eSAGE as part of their office visit at the Center for Cognitive and Memory Disorders.
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
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Subject population
Males and females 50 years of age and over who complete the eSAGE as part of their office visit at the Center for Cognitive and Memory Disorders.
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A self-administered digital assessment that evaluates multiple cognitive domains: orientation, language, memory, executive function, calculations, abstraction, and visuospatial abilities, through multiple questions.
Additionally, it includes the collection of six clinical variables: education, gender, race, family history of dementia, stroke, and emotion.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Area Under the Curve (AUC) for the ROC analysis in predicting subjects with cognitive impairment from cognitively normal subjects.
Time Frame: 1 day visit
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AUC ranges in value from 0 to 1
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1 day visit
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Douglas Scharre, Ohio State University
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2023H0249
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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