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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
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Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers

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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Anna-Katharine Brem1,2, Zunera Khan3, Ellie Pickering4

  • 1University Hospital of Old Age Psychiatry, University of Bern, Bern, Switzerland.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

The PREDICTOM study uses artificial intelligence (AI) to screen for Alzheimer's disease (AD) risk using home-based biomarkers. Early results show potential for differentiating high-risk individuals for timely intervention.

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Biomarker Discovery

Background:

  • Early detection of Alzheimer's disease (AD) is a critical unmet medical need.
  • Existing screening methods often lack accessibility and scalability for widespread early detection.

Purpose of the Study:

  • To develop and validate an AI-driven screening platform for predicting and detecting AD.
  • To extend AD screening to a home-based setting using novel and established biomarkers.

Main Methods:

  • The PREDICTOM study is a pan-European cohort of 4000 at-risk individuals over 50.
  • Level 1 involves home-based digital and physiological biomarker assessments.
  • AI algorithms will stratify participants into high and low AD risk groups for further in-clinic assessment (Level 2) and confirmation (Level 3).

Main Results:

  • An interim analysis will include data from approximately 1000 participants across the AD risk spectrum.
  • Initial findings will focus on the accuracy of at-home measures in differentiating risk stages.

Conclusions:

  • The PREDICTOM study aims to provide significant insights into the diagnostic accuracy of at-home AD screening tools.
  • The platform has the potential to revolutionize early AD detection and management through accessible, AI-powered risk stratification.