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Stepwise identification of prodromal dementia: Testing a practical model for primary care. | LitMetric

Stepwise identification of prodromal dementia: Testing a practical model for primary care.

J Alzheimers Dis

Department of Counseling and School Psychology, University of Massachusetts Boston, Boston, MA, USA.

Published: December 2024

AI Article Synopsis

  • Prodromal dementia is often missed in primary care, prompting a need for effective detection methods.
  • The study created a clinical model using the Functional Activities Questionnaire (FAQ) and Montreal Cognitive Assessment (MoCA) to improve identification of early dementia stages.
  • Results showed the proposed "step-down" screening model significantly outperformed alternative methods, suggesting it could efficiently support primary care in diagnosing dementia amidst growing treatment options and demand.

Article Abstract

Background: Prodromal dementia is largely underdiagnosed in primary care.

Objective: To develop a clinical model for detecting prodromal dementia within the operative boundaries of primary care practice.

Methods: The study employed the Functional Activities Questionnaire (FAQ) and Montreal Cognitive Assessment (MoCA) to evaluate a "functional-cognitive" step-down screening model, in which the MoCA is administered subsequent to reported symptoms on the FAQ. It classified participants from the Alzheimer's Disease Imaging Initiative to three diagnostic categories: (1) healthy cognition (n = 396), (2) mild cognitive impairment without conversion (n = 430), and (3) prodromal dementia assessed 24 months before diagnosis (n = 164).

Results: Analyses indicated that the step-down model (Model 1) performed significantly better than an alternative model that applied the FAQ as a single measure (Model 2) and compared well with another model that administered both screening measures to all participants (Model 3). Gradient Boosting Trees classifications yielded the following estimations for Model 1/Model 2/ Model 3, respectively: Sensitivity = 0.87/0.77/0.89, Specificity = 0.68/0.47/0.70, PPV = 0.73/0.40/0.75, NVP = 0.84/0.81/0.87, F1 Score = 0.79/0.52/0.81, AUC = 0.78/0.67/0.79.

Conclusions: These analyses support the proposed model. The study offers algorithms for validated measures, which were developed from a well characterized clinical sample. Their accuracy will likely improve further with new data from diverse clinical settings. These results can serve primary care in a timely manner in light of the recent advances in pharmacological treatment of dementia and the expected increase in demand for screening.

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Source
http://dx.doi.org/10.1177/13872877241297410DOI Listing

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