Introduction
Hearing and vision loss are independently associated with dementia, but the impact of dual sensory impairment (DSI) on dementia risk is not well understood.
Methods
Self‐reported measures of hearing and vision were taken from 2051 participants at baseline from the Gingko Evaluation of Memory Study. Dementia status was ascertained using standardized criteria. Cox models were used to estimate risk of dementia associated with number of sensory impairments (none, one, or two).
Results
DSI was significantly associated with higher risk of all‐cause dementia (hazard ratio [HR] = 1.86; 95% confidence interval [CI] = 1.25‐2.76) and Alzheimer's disease (HR = 2.12; 95% CI = 1.34‐3.36). Individually only visual impairment was independently associated with an increased risk of all‐cause dementia (HR = 1.32; 95% CI = 1.02‐1.71).
Discussion
Older adults with DSI are at a significantly increased risk for dementia. Further studies are needed to evaluate whether treatments can modify this risk.
Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer’s disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.
Introduction
Ophthalmic conditions and dementia appear to overlap and may share common pathways, but research has not differentiated dementia subtypes.
Methods
Diagnoses of cataracts, age‐related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma were based on medical histories and International Classification of Diseases, Ninth Revision (ICD‐9) codes for 3375 participants from the Cardiovascular Health Study. Dementia, including Alzheimer's disease (AD) and vascular dementia (VaD), was classified using standardized research criteria.
Results
Cataracts were associated with AD (hazard ratio [HR] = 1.34; 95% confidence interval [CI] = 1.01‐1.80) and VaD/mixed dementia (HR = 1.41; 95% CI = 1.02‐1.95). AMD was associated with AD only (HR = 1.87; 95% CI = 1.13‐3.09), whereas DR was associated with VaD/mixed dementia only (HR = 2.63; 95% CI = 1.10‐6.27).
Discussion
Differential associations between specific ophthalmic conditions and dementia subtypes may elucidate pathophysiologic pathways. Lack of association between glaucoma and dementia was most surprising from these analyses.
Key Points
Question
Is dual sensory impairment associated with risk of dementia, including Alzheimer disease and vascular dementia, among older adults?
Findings
In this cohort study that included 2927 adults aged 65 years and older, dual sensory impairment was associated with a 160% increased risk for all-cause dementia and a 267% increased risk for Alzheimer disease.
Meaning
These findings suggest that assessment of both hearing and vision may help to identify older adults who are at high risk of developing dementia.
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