Publications by authors named "C Birkenbihl"
Cognitive resilience (CR) describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer's disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model's residuals.
View Article and Find Full Text PDFDementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive decline and impairs patients' daily life. Affected patients show great heterogeneity in their symptomatic progression, which hampers the identification of efficacious treatments in clinical trials. Using artificial intelligence approaches to enable clinical enrichment trials serves a promising avenue to identify treatments.
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- The study investigates the relationship between changes in β-amyloid (Aβ) levels and cognitive decline over time, highlighting that Aβ accumulation is linked to subsequent cognitive deterioration in older adults.
- Researchers utilized sophisticated statistical models on data from a long-term study of 352 cognitively normal older participants, revealing that short-term changes in Aβ are more impactful on cognition than traditional measurements of Aβ burden and tau levels.
- Contrary to previous findings, the study found no significant link between tau levels in the medial temporal lobe and cognitive performance, suggesting that understanding cognitive decline requires looking at dynamic changes rather than static measures.
Article Synopsis
- Cognitive resilience is when people don't show mental decline even if they have signs of Alzheimer's in their brains.
- Measuring cognitive resilience is tricky because it can't be seen directly, and one common method used might give wrong results.
- The new method we suggest uses machine learning to improve how we measure cognitive resilience, making it more accurate and relying less on guesses about the data.
Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs.
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