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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Clinical predictors of cognitive decline in patients with mild cognitive impairment: the Chongqing aging study
Ling Li1, Yanjiang Wang, Jiachuan Yan
1Department of Neurology, Third Military Medical University, Daping, Chongqing, China.
Abstract:
Mild cognitive impairment (MCI) is considered as the early stage of dementia which currently has no effective treatments. Reducing progression of cognitive decline at the MCI stage could be an important strategy for preventing conversion to dementia. The goal of this work was to screen for clinical predictors indicating the prognosis of MCI comprehensively; therefore, we assumed vascular risk factors (VRFs), carotid stenosis, and white matter changes (WMC) to be independent predictors. A total of 257 patients with MCI underwent collection of VRF information, neuropsychological evaluation, computed tomography angiography (CTA) to investigate carotid stenosis, and magnetic resonance imaging (MRI) to identify severity of WMC. After a 3-year follow-up period, the neuropsychological evaluation, CTA, and MRI were repeated to assess the progression of cognitive decline, carotid stenosis, and WMC. The conversion rate from MCI to dementia was 11.65% per year, and the conversion rate from MCI to Alzheimer's disease was 7.05% per year in our cohort. Cognitive decline (in terms of changes in Mini Mental State Examination scores) was associated with diabetes mellitus (p = 0.004), baseline WMC severity (p < 0.001), baseline carotid stenosis (p < 0.001), and WMC severity change (p < 0.001). Besides, diabetes, baseline WMC severity, baseline moderate-to-severe carotid stenosis, and carotid stenosis change during follow-up were predictors of conversion from MCI to dementia. Given the potential clinical predictors, our findings could imply that controlling blood glucose, removing carotid stenosis, and improving cerebral perfusion could be effective measures to delay cognitive decline in patients with MCI and prevent conversion from MCI to dementia.
Insights
Identifying early predictors of dementia is crucial. Vascular risk factors, carotid stenosis, and white matter changes significantly impact cognitive decline in mild cognitive impairment (MCI) patients, suggesting potential interventions.
Area of Science:
- Neurology
- Gerontology
- Radiology
Background:
- Mild cognitive impairment (MCI) represents an early stage of dementia with no current effective treatments.
- Early intervention in MCI is key to preventing progression to dementia.
- Vascular risk factors (VRFs), carotid stenosis, and white matter changes (WMC) are hypothesized predictors of MCI prognosis.
Purpose of the Study:
- To comprehensively screen for clinical predictors of MCI prognosis.
- To investigate the independent predictive roles of VRFs, carotid stenosis, and WMC in MCI progression.
- To identify factors associated with cognitive decline and conversion to dementia in MCI patients.
Main Methods:
- 257 MCI patients underwent baseline assessments: VRF data, neuropsychological tests, computed tomography angiography (CTA) for carotid stenosis, and magnetic resonance imaging (MRI) for WMC severity.
- A 3-year follow-up included repeat assessments of cognitive function, carotid stenosis, and WMC.
- Statistical analysis identified predictors of cognitive decline and MCI conversion.
Main Results:
- The annual conversion rate from MCI to dementia was 11.65%, and to Alzheimer's disease was 7.05%.
- Cognitive decline correlated with diabetes mellitus, baseline WMC severity, baseline carotid stenosis, and WMC severity change.
- Diabetes, baseline WMC severity, moderate-to-severe baseline carotid stenosis, and changes in carotid stenosis predicted conversion to dementia.
Conclusions:
- Controlling blood glucose levels is important for managing MCI.
- Addressing carotid stenosis and improving cerebral perfusion may delay cognitive decline in MCI.
- Identifying and managing VRFs, WMC, and carotid stenosis are crucial for preventing dementia conversion from MCI.
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