title: Clinical predictors of cognitive decline in patients with mild cognitive impairment: the Chongqing aging study.
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.
authors.affiliation: Department of Neurology, Third Military Medical University, Daping, Chongqing, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.forename: Yanjiang
authors.initials: Y
authors.lastname: Wang
authors.forename: Jiachuan
authors.initials: J
authors.lastname: Yan
authors.forename: Yang
authors.initials: Y
authors.lastname: Chen
authors.forename: Rui
authors.initials: R
authors.lastname: Zhou
authors.forename: Xu
authors.initials: X
authors.lastname: Yi
authors.forename: Qianqian
authors.initials: Q
authors.lastname: Shi
authors.forename: Huadong
authors.initials: H
authors.lastname: Zhou
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology*; D002561:Cerebrovascular Disorders / Q000150:complications / Q000453:epidemiology; D002681:China / Q000453:epidemiology; D003072:Cognition Disorders / Q000175:diagnosis* / Q000453:epidemiology* / Q000209:etiology; D015331:Cohort Studies; D003704:Dementia / Q000175:diagnosis; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011569:Psychiatric Status Rating Scales; D011859:Radiography; D012307:Risk Factors; D015898:Tomography Scanners, X-Ray Computed