Integrating eSAGE With EHR Data Using Machine Learning for the Early Detection and Monitoring of Cognitive Impairment in Individuals

Part of paid clinical trials in Columbus, Ohio.

Sponsor
Douglas Scharre
Study ID
NCT06017505
Status
Enrolling By Invitation

Conditions

Eligibility Criteria

Sex
ALL
Age
50 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • electronic self administered gerocognitive examination (eSAGE) — DIAGNOSTIC_TEST
    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.

Study Details

The goal of this observational trial is to leverage the electronic Self-Administered Gerocognitive Examination (eSAGE), a variety of metadata (a set of data that describes and gives information about other data) collected during eSAGE testing, electronic health records (EHR) information, and advanced machine learning (ML) techniques to develop a new tool that can aid in early-stage prediction of individuals with cognitive impairments.

Key Dates

Start date
Sep 1, 2024
Status verified
Mar 2025
Primary completion
Sep 30, 2027
Completion
Sep 30, 2027

Study Design

Enrollment
1,486 participants (estimated)

Arms

  • Arm: 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.

Primary Outcome Measure

Area Under the Curve (AUC) for the ROC analysis in predicting subjects with cognitive impairment from cognitively normal subjects. [ Time Frame: 1 day visit ]

Locations (1)

FacilityCityStateZIPSite coordinators
Nicole VrettosColumbusOhio43123-

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