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

INTRODUCTION: We compared the accuracy of pattern-recognition protocols to prospectively identify Alzheimer's disease and related dementias (ADRD) and differentiate these from normal aging or stroke. METHODS: Patterns of cognitive decline in cognitively unimpaired participants who completed ≥ 5 assessments for the Health and Retirement Study were examined to identify dementia/stroke and compared to both recorded clinical and objective diagnoses of amnestic cognitive impairment (aCI) and dementia. We report prevalence and sensitivity/specificity to detect new-onset ADRD and stroke. RESULTS: ADRD-related accelerated cognitive decline was identified in 372 (14.6%) participants, while stepwise decline consistent with stroke was identified in 917 (36.1%) participants. Accelerated decline was found preceding 75.8%/76.7% cases of aCI and objective dementia, respectively. Sensitivity for accelerated decline to detect aCI/objective dementia was excellent (96.2%/91.9%). Stepwise decline preceded diagnosis with executive cognitive impairment (eCI)/clinical stroke in 40.0%/43.3% of participants, and sensitivity was moderate for eCI/clinical stroke (45.3%/58.8%). DISCUSSION: Longitudinal patterns of cognitive decline can help differentially diagnose ADRD from stroke in longitudinal studies of cognitive decline. Highlights: Pattern recognition identified 95.3% of all cases of dementia in this study. Sensitivity of accelerated cognitive decline to detect incident dementia was 94.3%. Differential diagnosis for dementia might begin to rely on longitudinal cognition. Pattern recognition worked in cases of clinically and algorithmically diagnosed dementia.