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Updated: Aug 19, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild Cognitive Impairment, Reversion Rates, and Associated Factors: Comparison of Two Diagnostic Approaches
Marieclaire Overton1, Benjamin Sjögren1, Sölve Elmståhl1
1Division of Geriatric Medicine, Department of Clinical Sciences in Malmö, Lund University, Skåne University Hospital, Malmö, Sweden.
Background:
As mild cognitive impairment (MCI) is typically used to identify prodromal stages of dementia, it is essential to identify MCI criteria with high diagnostic stability and prediction of dementia. Moreover, further investigation into pinpointing key factors for reversion is required to foresee future prognosis of MCI patients accurately.
Objective:
To explore disparities in diagnostic stability by examining reversion rates produced by two operationalizations of the MCI definition: the widely applied Petersen criteria and a version of the Neuropsychological (NP) criteria and to identify cognitive, lifestyle, and health related factors for reversion.
Methods:
MCI was retrospectively classified in a sample from the Swedish community-based study Good Aging in Skåne with the Petersen criteria (n = 744, median follow-up = 7.0 years) and the NP criteria (n = 375, median follow-up, 6.7 years), respectively. Poisson regression models estimated the effect of various factors on the likelihood of incident reversion.
Results:
Reversion rates were 323/744 (43.4%, 95% confidence intervals (CI): 39.8; 47.0) and 181/375 (48.3% 95% CI: 43.2; 53.5) for the Petersen criteria and NP criteria, respectively. Participants with impairment in a single cognitive domain, regular alcohol consumption, living with someone, older age, and lower body mass index had a higher likelihood of reverting to normal.
Conclusion:
Reversion rates were similar for Petersen and NP criteria indicating that one definition is not superior to the other regarding diagnostic stability. Additionally, the results highlight important aspects such as multiple domain MCI, cohabitation, and the role of alcohol on predicting the trajectory of those diagnosed with MCI.
Insights
Mild cognitive impairment (MCI) reversion rates were similar using Petersen and Neuropsychological (NP) criteria. Factors like single-domain impairment and alcohol consumption influenced reversion, aiding dementia prediction.
Area of Science:
- Gerontology
- Neurology
- Cognitive Science
Background:
- Mild cognitive impairment (MCI) is a critical prodromal stage for dementia.
- Accurate diagnostic criteria and understanding reversion factors are vital for prognosis.
- Further research is needed to identify key predictors of MCI reversion.
Purpose of the Study:
- Compare diagnostic stability of Petersen and Neuropsychological (NP) criteria for MCI.
- Investigate cognitive, lifestyle, and health factors associated with MCI reversion.
- Enhance prediction of dementia trajectory in MCI patients.
Main Methods:
- Retrospective classification of MCI using Petersen (n=744) and NP (n=375) criteria.
- Utilized data from the Swedish Good Aging in Skåne cohort study.
- Employed Poisson regression models to analyze reversion predictors.
Main Results:
- Reversion rates were 43.4% (Petersen) and 48.3% (NP criteria).
- Single-domain cognitive impairment, regular alcohol use, cohabitation, older age, and lower BMI predicted higher reversion likelihood.
- No significant superiority found between the two MCI criteria regarding diagnostic stability.
Conclusions:
- Petersen and NP criteria demonstrate comparable diagnostic stability for MCI.
- Factors like multiple domain impairment, cohabitation, and alcohol consumption are crucial for predicting MCI outcomes.
- Identifying reversion predictors improves prognostic accuracy for individuals with MCI.
