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Updated: Jun 23, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Outcome in subgroups of mild cognitive impairment (MCI) is highly predictable using a simple algorithm
Joanna Mitchell1, Robert Arnold, Kate Dawson
1Department of Clinical Neuroscience, Addenbrooke's Hospital, Cambridge, UK.
Abstract:
Although it is well recognized that MCI represents a risk state for subsequent dementia, estimates of conversion vary widely according to the diagnostic criteria employed. There are currently no simple cognitive predictors of high and low risk of progression. We followed 107 non-demented non-depressed subjects from an original cohort of 124--sub-classified as follows: pure amnestic MCI (22), multi-domain MCI (54), non-amnestic MCI (10) and worried well (21). At 2 years, outcome varied considerably. Of the multi-domain MCI group 59% progressed to dementia and only 5% improved. By contrast, in pure amnestic MCI only 18% progressed and 41% improved. Of non-amnestic MCI patients 70% improved. The best predictor of progression was a combination of the Addenbrooke's cognitive examination (ACE) and the paired associate learning task (PAL), which produced high negative predictive (90%) and sensitivity (94%) values. The results indicate very different outcomes according to whether patients have pure amnestic versus multi-domain MCI. While the latter is an aggressive disorder, the former is more benign and unstable even in a clinic setting. Patients with scores >88 on the ACE and/or <14 errors on the PAL can be confidently reassured of a good prognosis.
Insights
Mild cognitive impairment (MCI) progression to dementia varies. Multi-domain MCI has a high conversion rate, while pure amnestic MCI is more benign, with specific cognitive tests predicting prognosis.
Area of Science:
- Neurology
- Gerontology
- Cognitive Science
Background:
- Mild cognitive impairment (MCI) is a known risk factor for dementia.
- Current diagnostic criteria lead to varied estimates of MCI conversion rates.
- Simple cognitive predictors for high and low risk of MCI progression are lacking.
Purpose of the Study:
- To investigate the differing progression rates of various MCI subtypes.
- To identify simple cognitive predictors for MCI progression.
- To differentiate outcomes for pure amnestic MCI versus multi-domain MCI.
Main Methods:
- Followed 107 non-demented, non-depressed subjects classified into pure amnestic MCI, multi-domain MCI, non-amnestic MCI, and worried well groups.
- Assessed outcomes at 2 years, including progression to dementia and improvement.
- Utilized the Addenbrooke's Cognitive Examination (ACE) and Paired Associate Learning (PAL) task to identify predictors.
Main Results:
- Multi-domain MCI showed a 59% progression to dementia and 5% improvement.
- Pure amnestic MCI had an 18% progression rate and 41% improvement.
- Non-amnestic MCI patients demonstrated a 70% improvement rate.
- A combination of ACE and PAL scores provided high negative predictive (90%) and sensitivity (94%) values for progression.
Conclusions:
- Outcomes differ significantly between pure amnestic MCI (benign, unstable) and multi-domain MCI (aggressive).
- High ACE scores (>88) or low PAL errors (<14) indicate a good prognosis.
- These findings aid in differentiating MCI subtypes and predicting dementia risk.
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