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Clinical Manifestations.

Pierre N Tariot1, Melissa Petersen2, Darren R Gitelman3

  • 1Banner Alzheimer's Institute and University of Arizona College of Medicine, Phoenix, AZ, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 25, 2025
PubMed
Summary
This summary is machine-generated.

Digital cognitive assessments (DCAs) offer a scalable solution for early Alzheimer's disease detection, overcoming traditional test limitations. Implementation pathways are established to integrate these advanced tools into clinical practice for improved brain health.

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Area of Science:

  • Neurology and Neuroscience
  • Digital Health and Medical Technology
  • Public Health and Epidemiology

Background:

  • Early detection of cognitive impairment (CI) is crucial for Alzheimer's disease (AD) management, but traditional assessments have significant limitations.
  • Scalable, cost-effective, and time-efficient tools are needed to overcome barriers in diagnosis and intervention.
  • Digital cognitive assessments (DCAs) show promise for improving accuracy, reducing testing times, and lowering costs, but require a standardized framework for clinical adoption.

Purpose of the Study:

  • To advance the clinical adoption of Digital Cognitive Assessments (DCAs) for faster and more accurate diagnosis of cognitive impairment and Alzheimer's disease.
  • To develop practical implementation pathways for integrating DCAs into existing healthcare workflows.
  • To identify key facilitators and barriers for the successful integration of DCAs in clinical settings.

Main Methods:

  • A multidisciplinary workgroup, including experts in research, clinical practice, industry, and patient advocacy, was convened by the Global CEO Initiative on Alzheimer's Disease (CEOi).
  • The workgroup focused on developing implementation pathways for DCAs, considering facilitators and barriers to integration.
  • Pathways were designed for three distinct clinical contexts: initial CI detection, confirmatory diagnosis, and etiological evaluation of confirmed CI.

Main Results:

  • Clinical implementation pathways were developed for detecting CI, aiding in the diagnosis of mild cognitive impairment or dementia, and supporting the evaluation of neurodegenerative causes of CI, including AD.
  • These pathways integrate DCAs into primary and secondary care, offering flexible workflows adaptable to diverse healthcare system capabilities.
  • The framework aims to streamline adoption, enhance diagnostic accuracy, and ensure adaptability, emphasizing a holistic approach guided by clinician judgment and cumulative data.

Conclusions:

  • Digital cognitive assessments (DCAs) hold significant potential to revolutionize the detection and diagnosis of cognitive impairment and AD, surpassing the limitations of conventional methods.
  • Defined use cases and implementation pathways provide a robust foundation for the widespread clinical adoption of DCAs, contributing to global brain health initiatives.
  • Ongoing collaboration among stakeholders and expert consensus are vital for fully realizing the impact of DCAs in improving diagnostic capabilities and addressing pragmatic implementation considerations.