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

NCT06017505 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 1486

Last updated 2025-03-21

No results posted yet for this study

Summary

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.

Conditions

Interventions

DIAGNOSTIC_TEST

electronic self administered gerocognitive examination (eSAGE)

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.

Sponsors & Collaborators

  • Douglas Scharre

    lead OTHER

Principal Investigators

  • Douglas Scharre · Ohio State University

Eligibility

Min Age
50 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-01
Primary Completion
2027-09-30
Completion
2027-09-30

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06017505 on ClinicalTrials.gov