Cognivue Clinical Data : Cognivue

Cognivue Clinical Data

The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity⁴⁷

Authors: James E. Galvin, Michael J. Kleiman, Heather M. Harris, Paul W. Estes
Journal: Neurology and Therapy
Year Published: 2025

Key Findings: Demonstrates a new metric, the Cognivue^® Amyloid Risk Measure (CARM),^* which derives its score from several of Cognivue Clarity^®’s cognitive assessment subtests and was developed to predict the presence of amyloid in individuals with or without cognitive impairment. CARM combined with the overall Cognivue Clarity cognitive assessment score could help identify individuals with and without cognitive impairment due to AD or non-AD etiologies.

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Objective: To test whether Cognivue Clarity^® can differentiate True Controls, preclinical Alzheimer’s disease (pAD), mild cognitive impairment (MCI) due to Alzheimer’s disease (MCI-AD), AD, and MCI and dementia due to non-AD etiologies enrolled in the Bio-Hermes Study.

Study Design:

Focused on a sample of 887 participants in the Bio-Hermes Study for analyses—only those who completed Cognivue Clarity, as well as both amyloid PET scan and AD blood-based biomarkers were included in analyses
- Sample included cognitively normal individuals (True Controls), cognitively normal individuals with the presence of amyloid (preclinical AD or pAD), individuals with mild cognitive impairment (MCI), and mild Alzheimer’s disease (AD)/span>
Used results from three Cognivue Clarity subtests that are sensitive to the presence of amyloid along with age to develop a 4-point amyloid-specific marker called the Cognivue Amyloid Risk Measure (CARM)

Results Summary :

Cognivue Clarity reliably differentiated cognitively normal individuals from cognitively impaired individuals (p<0.001, Cohen’s d=0.732)
Cognivue Amyloid Risk Measure (CARM) reliably differentiated amyloid positive individuals from amyloid negative individuals by PET (p<0.001, Cohen’s d=0.618) and blood-based biomarkers (p’s<0.001)
Amyloid positivity and cognitive impairment increased across four CARM thresholds (p<0.001)
Divided four CARM thresholds into low (CARM1/CARM2) and high (CARM3/CARM4) categories; likelihood provided excellent discrimination for amyloid PET positivity (OR: 3.67; 95% CI 2.76-4.89)
CARM categories differentiated between True Controls, pAD, MCI-AD, AD, and cognitive impairment due to non-AD etiologies (x²=137.6, p<0.001)
- Majority of True Controls and non-AD etiologies falling in CARM1/CARM2, and majority of pAD, MCI-AD, and AD falling in CARM3/CARM4

Main Takeaways

Cognivue Clarity is able to detect individuals with cognitive impairment
- Three of the Cognivue Clarity subtests were benchmarked against amyloid PET and used to develop the CARM score which can predict the presence of amyloid
CARM combined with the overall Cognivue Clarity cognitive assessment score could help identify individuals with and without cognitive impairment due to AD or non-AD etiologies
- These findings underscore Cognivue Clarity’s ability to help screen for treatment protocols with anti-amyloid therapies, enrich clinical trial recruitment, and help to identify pAD for prevention studies

*Patent Pending

Cognivue Clarity^® Characterizes Amyloid Status and Preclinical Alzheimer’s Disease in Biomarker Confirmed Cohorts in the Bio-Hermes Study⁴¹

Authors: James E. Galvin, Michael J. Kleiman, Paul W. Estes, Heather M. Harris, Ernest Fung
Journal: Journal of Alzheimer’s Disease
Year Published: 2025

Key Findings: Demonstrates Cognivue Clarity^®’s ability to screen for individuals with cognitive impairment, characterize amyloid positive individuals, and detect Preclinical Alzheimer’s disease (AD). This has great potential as a cost- and time-effective strategy to screen and enroll in AD prevention trials.

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Objective: Examined differences in Cognivue Clarity performance (a) between amyloid positive and amyloid negative individuals, (b) whether Cognivue Clarity could differentiate True Controls (cognitively normal/amyloid negative), Preclinical AD (cognitively normal/amyloid positive), and MCI due to AD (MCI-AD, cognitively impaired/amyloid positive).

Study Design:

Focused on a sample size of 505 from the enrolled participants in the Bio-Hermes Study for analyses on the detection of Preclinical AD—only those who completed Cognivue Clarity, as well as both amyloid PET scans and blood-based biomarkers
Performance was compared between bio-marker-defined groups: True Controls – cognitively normal/amyloid negative (297); Preclinical AD – cognitively normal/amyloid positive (95); and MCI-AD – cognitively impaired/amyloid positive (113)

Results Summary:

Cognivue Clarity reliably differentiated amyloid positive individuals from amyloid negative individuals (p <0.001)
Cognivue Clarity global score differentiated True Controls versus Preclinical AD (p =0.014) and significantly differentiated between True Controls and MCI-AD (p <0.001) and between Preclinical AD versus MCI-AD (p <0.001)
Comparisons of 3-subtests of Cognivue Clarity significantly differentiated True Controls from Preclinical AD [Shape Discrimination (p =0.004), Visual Salience (p =0.008), Adaptive Motor Control (p =0.004)]
A composite score of the mean of the same 3-subtests more significantly differentiated True Controls from Preclinical AD (p <0.001)
Cognivue Clarity global score and the 3-subtest mean composite score showed moderate correlations with Amyloid PET (r = -0.433) and pTau217 (r = -0.400)
The 3-subtest mean composite score identified Preclinical AD in both White and Black participants
Cognivue Clarity demonstrated a significant correlation with both plasma phosphorylated Tau217 (pTau217) levels and the Amyloid Probability Score (APS)

Main Takeaways

Cognitive Clarity is able to distinguish between:
- Cognitively Normal/Amyloid Negative vs. Preclinical AD
- Cognitively Normal, MCI and Mild Dementia – regardless of amyloid status
Composite score of the 3-subtests can distinguish between Cognitively Normal/Amyloid Negative, Preclinical AD, and MCI-AD groups and has significant correlations with amyloid PET, and 2-plasma biomarkers (pTau217 and APS)
These findings underscore Cognivue Clarity’s ability to detect Preclinical AD, thereby enhancing early diagnosis and facilitating the development of targeted interventions.

Cognivue Clarity Characterizes Mild Cognitive Impairment and Alzheimer’s Disease in Biomarker Confirmed Cohorts in the Bio-Hermes Study³⁹

Authors: James E. Galvin, Michael J. Kleiman, Paul W. Estes, Heather M. Harris, Ernest Fung
Journal: Scientific Reports
Year Presented: 2024

Key Findings: Demonstrates Cognivue Clarity^®’s ability to reliably differentiate between the cognitively normal, MCI, and mild dementia groups regardless of amyloid status. Therefore, it can provide useful information for consideration for further evaluation with biomarkers and more detailed neuropsychological evaluation in both clinical research and clinical practice settings.

Cognitive Assessment with Cognivue Clarity^®: Psychometric Properties and Normative Ranges in a Diverse Population³⁵

Authors: James E. Galvin, Lun-Ching Chang, Paul W. Estes, Heather M. Harris, Ernest Fung
Journal: Journal of Alzheimer’s Disease
Year Presented: 2024

Key Findings: Supports the use of Cognivue Clarity^® as an easy-to-use, brief, and valid cognitive assessment that measure cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.

The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Detect the Presence of Amyloid in Clinical Samples with Cognivue Clarity^®40

Authors: James E. Galvin, MD, MPH; Michael J. Kleiman, PhD; Paul W. Estes; Heather M. Harris; and Ernest Fung, PsyD
Conference Poster: Clinical Trials on Alzheimer’s Disease Conference (CTAD)
Year Presented: 2024

Key Findings: Cognivue Clarity^® could be used to help screen older adults for treatment protocols with anti-amyloid therapies, enrich clinical trial recruitment before obtaining expensive biomarkers, and identify individuals likely to have preclinical AD for prevention studies in a valid, brief, and cost-effective fashion. View it in The Journal of Prevention of Alzheimer’s Disease, page 201.

Detection of Amyloid Status and Preclinical Alzheimer’s Disease Using Cognivue Clarity^®, An Adaptive Psychophysics Computerized Cognitive Battery in The Bio-Hermes Study³⁶

Authors: James E. Galvin, MD, MPH; Michael J. Kleiman, PhD; Paul W. Estes; Ernest Fung, PsyD; and Heather M. Harris
Conference Poster:The Alzheimer’s Association International Conference (AAIC)
Year Presented: 2024

Key Findings: Cognivue Clarity^® has great potential as an enrichment strategy for Alzheimer’s disease (AD) clinical trials testing amyloid-lowering therapies as well as for AD prevention.

Cognivue Clarity^® in the Detection of Biomarker-Confirmed Mild Cognitive Impairment and Alzheimer’s Disease³⁴

Authors: James E. Galvin, MD, MPH; Michael J. Kleiman, PhD; Heather M. Harris; Paul W. Estes
Conference Poster:The American Academy of Neurology (AAN) Annual Meeting
Year Presented: 2024

Key Findings: Cognivue Clarity^® discriminated healthy controls from those with Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD), strongly correlated with AD biomarkers, and had strong psychometric properties.
Data is also published in Neurology, Volume 102, Number 17 Supplement 1, 2024. View it in Neurology

Advancing Computerized Cognitive Assessment with Cognivue: Enhanced Normative Range Data Sets from a Diverse Population Improve Sensitivity and Patient Profiling³¹

Authors: James E. Galvin, MD, MPH, Joel Raskin, MD, Paul Estes, Robert Parody PhD, Catherine Tallmadge, Heather Harris
Conference Poster: Clinical Trials for Alzheimer’s Disease (CTAD) Annual Conference
Year Presented: 2023

Key Findings: Cognitive assessment with Cognivue Clarity^® among a diverse population of study participants enhances normative range data sets to improve sensitivity and patient profiling.
Data is also published in The Journal of Prevention of Alzheimer’s Disease, Volume 10, Supplement 1, 2023. View it in The Journal of Prevention of Alzheimer’s Disease, page 225.

Bridging the Assessment Gap: Newly Developed Neuropsychiatric Cognitive Assessments on the Cognivue Platform Show Strong Correlation with Traditional Gold Standard Tests²

Authors: : James E. Galvin, MD, MPH, Paul Estes, Shiva Pal, Seth Wideman, Catherine Tallmadge, Heather Harris
Conference Poster: Clinical Trials for Alzheimer’s Disease (CTAD) Annual Conference
Year Presented: 2023

Key Findings: Cognitive assessment with the computerized Cognivue Clarity^® device showed strong correlation with traditional gold-standard cognitive tests and excellent internal consistency and reliability.
Data is also published in The Journal of Prevention of Alzheimer’s Disease, Volume 10, Supplement 1, 2023. View it in The Journal of Prevention of Alzheimer’s Disease, page 169.

Cognitive Testing in Diverse Populations to Further the Objective and Clinical Understanding Study (FOCUS)²⁹

Authors: James E. Galvin, MD, MPH; Velocity Clinical Research; Paul W. Estes; Heather M. Harris
Conference Poster: Alzheimer’s Association International Conference (AAIC)
Year Presented: 2023

Key Findings: Historically underserved and underrepresented populations have a 37% research participation rate in the FOCUS cognitive testing study in the United States (US).
Data is also published in Alzheimer’s & Dementia, Volume 19, Issue S24, Supplement: Developing Topics December 2023. View it in Alzheimer’s & Dementia.

Community Pharmacists Expand Access to Cognitive Function Assessments with the Cognivue Clarity^® Device³⁰

Authors: Amina Abubaka, PharmD, AAHIVP; Saswat Kabisatpathy, PharmD; Susan Lutz; Jessica Sinclair, PharmD
Conference Poster: Alzheimer’s Association International Conference (AAIC)
Year Presented: 2023

Key Findings: With training and use of the Cognitive Clarity^® device, pharmacists can easily provide an objective cognitive function assessment. Widespread implementation of pharmacy-based computerized cognitive testing could greatly expand access to meet the brain health needs of the growing senior population including patients living in medically underserved and rural areas.
Data is also published in Alzheimer’s & Dementia, Volume 19, Issue S24, Supplement: Developing Topics December 2023. View it in Alzheimer’s & Dementia.

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