Evidence map›Paper›PMID 40192926›Full record

ArticleNeurology and therapy2025

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

James E Galvin, Michael J Kleiman, Heather M Harris, Paul W Estes

Registry-linked trialAbstract read
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In one paragraph

Article in Neurology and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04733989 (Development of a Biomarker Database to Investigate Aß, P-tau, and NfL Blood-Based Biomarkers and Digital Biomarkers in Older Participants Screened for Preclinical Alzheimer's Disease), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04733989 completednot on this map

Development of a Biomarker Database to Investigate Aß, P-tau, and NfL Blood-Based Biomarkers and Digital Biomarkers in Older Participants Screened for Preclinical Alzheimer's Disease (AD), Prodromal AD, or Mild AD

TypeobservationalSponsorGAP Innovations, PBCRan2021 to 2022Enrolled1,002ConditionsAlzheimer Disease, Alzheimer Disease, Early Onset, Mild Cognitive Impairment, Memory LossArmsBiomarker Data Collection
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

James E GalvinDepartment of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, 7700 W Camino Real, Suite 200, Boca Raton, FL, 33433, USA. jeg200@miami.edu.ORCID http://orcid.org/0000-0001-5678-245X
Michael J KleimanDepartment of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, 7700 W Camino Real, Suite 200, Boca Raton, FL, 33433, USA.
Heather M HarrisCognivue, Inc, 7911 Rae Blvd, Victor, NY, 14564, USA.
Paul W EstesCognivue, Inc, 7911 Rae Blvd, Victor, NY, 14564, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAt the present time, clinical detection of individuals who have amyloid in their brain is not possible without expensive biomarkers. The objective of the study was to test whether Cognivue Clarity

methodsA total of 887 individuals completed Cognivue Clarity, amyloid PET scan, and blood-based AD biomarkers. Three Cognivue Clarity subtests differentiated between True Controls and pAD, and between cognitive impairment due to AD versus non-AD processes. This finding was leveraged to develop an amyloid-specific marker, combining the three subtests with age using machine learning to create the 4-point Cognivue Amyloid Risk Measure (CARM).

resultsCognivue Clarity discriminated cognitively normal from cognitively impaired individuals (p < 0.001, Cohen's d = 0.732). The CARM differentiated between individuals with amyloid and without amyloid 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). Dichotomizing CARM thresholds into low (CARM1/CARM2) and high (CARM3/CARM4) 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 (χ

conclusionsCognivue Clarity detects individuals with cognitive impairment, and a derivation benchmarked against amyloid PET was used to develop the CARM to predict the presence of amyloid. Combining the CARM and the Cognivue Clarity overall score could help identify individuals with and without cognitive impairment due to AD or non-AD etiologies, help screen for treatment protocols with anti-amyloid therapies, enrich clinical trial recruitment, and help to identify pAD for prevention studies.

trial registrationClinicalTrials. gov identifier, NCT04733989.

Indexed as

Alzheimer’s diseaseAmyloid PETBio-HermesCognitive assessmentCognivueDigital biomarkerMild Cognitive ImpairmentPreclinical Alzheimer’s disease

Identifiers

PMID40192926
PMCPMC12089551

What Socratic holds

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LicenceCC BY-NC
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.