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Updated: Aug 20, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A Critical Review of Neuropsychological Actuarial Criteria for Mild Cognitive Impairment
Anne R Carlew1, Alyssa Kaser1, Jeff Schaffert1
1Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Background:
The concept of mild cognitive impairment (MCI) has evolved since its original conception. So, too, have MCI diagnostic methods, all of which have varying degrees of success in identifying individuals at risk of conversion to dementia. The neuropsychological actuarial method is a straightforward diagnostic approach that has shown promise in large datasets in identifying individuals with MCI who are likely to have progressive courses. This method has been increasingly applied in various iterations and samples, raising questions of how best to apply this method and when caution should be used.
Objective:
Our objective was to review the literature investigating use of the neuropsychological actuarial method to diagnose MCI to identify strengths and weaknesses of this approach, as well as highlight areas for further research.
Methods:
Databases PubMed and PsychInfo were systematically searched for studies that compared the neuropsychological actuarial method to some other diagnostic method.
Results:
We identified 13 articles and extracted relevant study characteristics and findings. Existing literature was reviewed and integrated, with focus on the neuropsychological actuarial method's performance relative to existing diagnostic methods/criteria as well as associations with longitudinal outcomes and biomarkers. Tables with pertinent methodological information and general findings are also provided.
Conclusion:
The neuropsychological actuarial method to diagnose MCI has shown utility some in large-scale homogenous databases compared to research criteria. However, its standing relative to consensus diagnostic methods is unclear, and emerging evidence suggests the neuropsychological actuarial method may be more prone to diagnostic errors in more demographically diverse populations.
Insights
The neuropsychological actuarial method shows promise for diagnosing mild cognitive impairment (MCI) in large, homogenous groups. However, its effectiveness in diverse populations and compared to consensus methods requires further investigation.
Area of Science:
- Neuroscience
- Gerontology
- Psychology
Background:
- Mild cognitive impairment (MCI) diagnosis methods have evolved, with varying success in predicting dementia conversion.
- The neuropsychological actuarial method offers a promising approach for identifying progressive MCI in large datasets.
- Increasing application of this method raises questions about optimal usage and potential limitations.
Approach:
- Systematic literature search of PubMed and PsychInfo databases.
- Inclusion of studies comparing the neuropsychological actuarial method with other diagnostic approaches.
- Extraction and integration of study characteristics, findings, and performance relative to existing criteria.
Key Points:
- The neuropsychological actuarial method demonstrates utility in large, homogenous databases for MCI diagnosis.
- Its performance relative to established consensus diagnostic methods remains unclear.
- Emerging evidence indicates potential for increased diagnostic errors in demographically diverse populations.
Conclusions:
- The neuropsychological actuarial method is a valuable tool for MCI diagnosis in specific contexts.
- Further research is needed to clarify its standing against consensus methods and its applicability across diverse demographics.
- Understanding limitations is crucial for accurate MCI diagnosis and predicting progression to dementia.
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