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Updated: Jun 24, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Functional and cognitive criteria produce different rates of mild cognitive impairment and conversion to dementia
J Saxton1, B E Snitz, O L Lopez
1Department of Neurology, University of Pittsburgh, 3471 Fifth Avenue, Suite 811, Pittsburgh, PA 15213, USA. saxtonja@upmc.edu
Objective:
To compare rates of mild cognitive impairment (MCI) and rates of progression to dementia using different MCI diagnostic systems.
Methods:
MCI was investigated at baseline in 3063 community dwelling non-demented elderly in the Ginkgo Evaluation of Memory (GEM) study who were evaluated every 6 months to identify the presence of dementia. Overall MCI frequency was determined using (1) a Clinical Dementia Rating (CDR) score of 0.5 and (2) neuropsychological (NP) criteria, defined by impairment on standard cognitive tests.
Results:
40.2% of participants met CDR MCI criteria and 28.2% met NP MCI criteria (amnestic MCI = 16.6%). 15.7% were classified as MCI by both criteria and 47.4% as normal by both. Discordant diagnoses were observed in 24.5% who met NP normal/CDR MCI and in 12.4% who met NP MCI/CDR normal. Factors associated with CDR MCI among NP normal included lower education, lower NP scores, more instrumental activities of daily living impairment, greater symptoms of depression and subjective health problems. Individuals meeting NP MCI/CDR normal were significantly more likely to develop dementia over the median follow-up of 6.1 years than those meeting NP normal/CDR MCI.
Conclusions:
Different criteria produce different MCI rates and different conversion rates to dementia. Although a higher percentage of MCI was identified by CDR than NP, a higher percentage of NP MCI progressed to dementia. These findings suggest that the CDR is sensitive to subtle changes in cognition not identified by the NP algorithm but is also sensitive to demographic and clinical factors probably leading to a greater number of false positives. These results suggest that identifying all individuals with CDR scores of 0.5 as Alzheimer's disease is not advisable.
Insights
Different diagnostic criteria for mild cognitive impairment (MCI) yield varying prevalence and dementia conversion rates. Neuropsychological (NP) criteria identified fewer MCI cases but showed higher progression to dementia compared to the Clinical Dementia Rating (CDR).
Area of Science:
- Neurology
- Gerontology
- Cognitive Science
Background:
- Mild cognitive impairment (MCI) is a transitional stage between normal aging and dementia.
- Accurate diagnosis of MCI is crucial for early intervention and understanding disease progression.
- Various diagnostic systems exist, potentially leading to discrepancies in identification and prognosis.
Purpose of the Study:
- To compare the rates of mild cognitive impairment (MCI) and subsequent progression to dementia using distinct diagnostic criteria.
- To evaluate the concordance and discordance between the Clinical Dementia Rating (CDR) and neuropsychological (NP) criteria for MCI.
- To identify factors associated with MCI diagnoses and their predictive value for dementia development.
Main Methods:
- The Ginkgo Evaluation of Memory (GEM) study enrolled 3063 non-demented elderly individuals.
- MCI was assessed at baseline using both CDR (score of 0.5) and NP criteria (standard cognitive tests).
- Participants were followed for dementia development over a median of 6.1 years.
Main Results:
- 40.2% met CDR MCI criteria, while 28.2% met NP MCI criteria; only 15.7% met both.
- Significant discordance was observed, with 24.5% classified as NP normal/CDR MCI and 12.4% as NP MCI/CDR normal.
- Individuals diagnosed with NP MCI but CDR normal were more likely to progress to dementia.
Conclusions:
- Different MCI diagnostic systems result in varied prevalence and dementia conversion rates.
- While CDR identifies more MCI cases, NP criteria better predict progression to dementia.
- CDR may capture subtle cognitive changes but is also susceptible to demographic and clinical confounders, suggesting caution in its sole use for diagnosing Alzheimer's disease.
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