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Updated: Jul 7, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Frequency and course of mild cognitive impairment in a multiethnic community
Jennifer J Manly1, Ming-X Tang, Nicole Schupf
1Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA.
Objective:
To examine incidence rates and antecedents of mild cognitive impairment (MCI) and Alzheimer's disease (AD) among diverse elders without dementia at the initial visit, and to examine the characteristics of elders with MCI who reverted to normal on follow-up examination.
Methods:
A total of 2,364 Caribbean Hispanic, black, or non-Hispanic white subjects, aged 65 or older, who were free of dementia at initial evaluation were followed up every 18 to 24 months. Incidence rate of MCI and AD was determined by examination of neurological, medical, psychiatric, and neuropsychological function.
Results:
Over 10,517 person-years, 21% of normal elderly subjects progressed to MCI (annual incidence rate, 5.1%; 95% confidence interval, 4.6-5.6%). Of those with MCI initially, 21.8% were subsequently diagnosed with AD (annual incidence rate, 5.4%; 95% confidence interval, 4.7-6.3%), 47% remained unchanged, and 31% reverted to normal. Those with MCI were 2.8 times more likely to experience development of AD than normal elderly subjects. MCI with impairment in memory and at least one other cognitive domain was associated with greatest risk for progression to AD and was also least likely to revert to normal at follow-up. Consistent diagnosis of MCI or incident probable or possible AD was 60% sensitive and 94% specific for the pathological diagnosis of AD.
Interpretation:
Impaired memory and language were useful predictors of transition to AD. Reversion to normal from MCI was frequent, but those with impairment in more than one cognitive domain were more likely to progress or remain impaired than those with single-domain impairment. Clinical diagnosis of MCI does not always predict AD neuropathology.
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