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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Revised criteria for mild cognitive impairment: validation within a longitudinal population study
Sylvaine Artero1, Ronald Petersen, Jacques Touchon
1INSERM E361, Hôpital Gui-de-Chauliac, Université de Montpellier-1, Montpellier, France. artero@montp.inserm.fr
Background:
Mild cognitive impairment (MCI) refers to the transitional zone between normal ageing and dementia. Current criteria perform poorly within the general population setting. Revisions have been proposed based on results obtained from clinical and epidemiological studies.
Objective:
To evaluate revised diagnostic criteria for mild cognitive impairment (MCI-R) incorporating changes in activity level and non-mnesic cognitive functioning.
Method:
MCI-R subjects were recruited from a representative network of general practitioners in the south of France. A computerized neuropsychometric examination was given. At 2 years of follow-up, a diagnosis of dementia was made by a neurologist using DSM-IIIR criteria and without knowledge of the results of the cognitive testing. Rates of conversion to incident dementia were assessed by receiver operating characteristics analysis.
Results:
The MCI-R prevalence was found to be 16.6% using revised criteria. A significantly better prediction of transition to dementia (AUC = 0.80, sensitivity: 95%, specificity: 66%) was obtained with MCI-R than with the previous MCI criteria (AUC = 0.48, sensitivity: 5%, specificity: 91%). The predictive power was found to increase when MCI subtypes were combined.
Conclusion:
Incorporating the possibility of change in activity level and alteration of non-mnesic cognitive functions have been found to ameliorate the original algorithm and better define subjects converting to dementia. This definition may be applicable to both clinical and population research.
Insights
Revised criteria for mild cognitive impairment (MCI-R) significantly improve dementia prediction in general populations. These updated guidelines better identify individuals likely to transition to dementia, aiding clinical and population research.
Area of Science:
- Neurology
- Gerontology
- Cognitive Science
Background:
- Mild cognitive impairment (MCI) represents a stage between normal aging and dementia.
- Current MCI diagnostic criteria show limitations in general population settings.
- Revisions to MCI criteria are being explored based on clinical and epidemiological data.
Purpose of the Study:
- To assess revised diagnostic criteria for mild cognitive impairment (MCI-R).
- The revised criteria incorporate changes in activity levels and non-mnesic cognitive functions.
- To evaluate the diagnostic utility of MCI-R in predicting dementia conversion.
Main Methods:
- Subjects were recruited from general practitioners in southern France.
- A computerized neuropsychometric examination was administered.
- Neurologists diagnosed dementia using DSM-IIIR criteria after a 2-year follow-up, independent of cognitive test results.
- Receiver operating characteristics analysis assessed dementia conversion rates.
Main Results:
- The prevalence of MCI-R was 16.6%.
- MCI-R demonstrated significantly improved prediction of dementia transition (AUC = 0.80) compared to previous MCI criteria (AUC = 0.48).
- Predictive power increased when MCI subtypes were combined.
Conclusions:
- Revised criteria (MCI-R) enhance the original algorithm for defining MCI.
- The updated criteria better identify individuals progressing to dementia.
- MCI-R criteria show potential applicability in both clinical practice and population-based studies.
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