Accuracy of pattern-based dementia diagnostic protocols: Using longitudinal data to infer etiology of Alzheimer’s disease and related dementia as compared to stroke or normal aging

Introduction The goal of this study was to compare accuracy for pattern-recognition protocols to prospectively identify dementia due to Alzheimer’s disease and related dementias (ADRD) or stroke.

Methods We used data from cognitively unimpaired respondents who completed at least 5 cognitive assessments during waves 3–12 of the Health and Retirement Study (HRS), a longitudinal study of older US residents. Participants were assessed at wave 12 (in 2019) for cognitive status. Patterns of participants’ cognitive decline were analyzed to differentially identify ADRD and stroke and were compared against self-reported and objective diagnoses of amnestic, executive, and multidomain mild cognitive impairment (MCI) and ADRD. We reported sensitivity/specificity to detect new-onset dementia at the final wave of observation.

Results After applying inclusion/exclusion criteria, 43 (1.69%) of cognitively unimpaired participants developed dementia, while 165 (6.49%) developed amnestic MCI. Patterns of cognitive decline consistent with ADRD affected 372 (14.6%) of respondents, while patterns of cognitive decline consistent with stroke were evident in 917 (36.1%) participants. ADRD- consistent cognitive declines were evident in 75.8% and 76.7% cases of amnestic MCI and dementia, respectively, though only 24.5% reported receiving a clinical diagnosis of dementia. Sensitivity/Specificity of ADRD was 94.3%/87.0% when detecting dementia without stroke.

Discussion This study implies that we can reliably use longitudinal patterns of cognitive decline to differentially diagnose ADRD from Stroke in most participants with dementia.

Competing Interest Statement
The authors have declared no competing interest.

Funding Statement
The study was funded by the National Institutes of Health (NIH/NIA RF1 AG058595) and by the Alzheimer's Association.