Alzheimer’s disease (AD) is traditionally thought of as a neurodegenerative disease. Recent evidence shows that beta amyloid-independent vascular changes and beta amyloid-dependent neuronal dysfunction both equally influence the disease, leading to loss of structural and functional connectivity. White matter changes (WMCs) in the brain are commonly observed in dementia patients. The effect of vascular factors on WMCs and the relationship between WMCs and severity of AD in patients remain to be clarified. We recruited 501 clinically diagnosed probable AD patients with a series of comprehensive neuropsychological tests and brain imaging. The WMCs in cerebral CT or MRI were rated using both the modified Fazekas scale and the combined CT-MRI age related WMC (ARWMC) rating scale. Periventricular WMCs were observed in 79.4% of the patients and deep WMCs were also seen in 48.7% of the patients. WMC scores were significantly higher in the advanced dementia stage in periventricular WMCs (p = 0.001) and total ARWMCs (p < 0.001). Age and disease severity were both independently associated with WMCs score, particularly in the total, frontal and parieto-occipital areas. Vascular factors including hypertension, diabetes mellitus, and gender were not significantly associated with WMCs. In conclusion, both age and severity of dementia were significantly associated with WMCs in AD patients. These associations highlight future research targets.

Background: As the average life expectancy of global citizens has increased, the prevalence of dementia has increased rapidly. The number of patients with dementia has increased by 6.7 times, reaching 300,000 in the past three decades in Taiwan. To realize the latest actual situation, the need for institutional care for elderly patients with dementia, and also a reference basis for government agencies to formulate dementia-related care policies, we investigated the institutional prevalence of dementia. Methods: We randomly sampled 299 out of the 1607 registered long-term care facilities including senior citizens’ institutions, nursing homes, and veteran homes in every administrative region of Taiwan. Then, a two-phase survey including MMSE screening, CDR, and clinical confirmation was conducted on each subject from 2019 to 2020. Results: Among 5753 enrolled subjects, 4765 from 266 facilities completed the examinations with a response rate of 82.8%. A total of 4150 subjects were diagnosed with dementia, 7.4% of whom had very mild dementia. The prevalence of all-cause dementia, including very mild dementia, was 87.1% in all facilities, 87.4% in senior citizens’ institutions, 87.1% in nursing homes, and 83.3% in veteran homes. Advanced age, low education, hypertension, Parkinsonism, respiratory disease, stroke, and intractable epilepsy were associated with dementia risk. Conclusions: We show that in an aged society, the prevalence of all-cause dementia in long-term care institutions can be as high as 87.1%. This study was completed before the outbreak of COVID-19 and provides a precious hallmark for future epidemiological research. We recommend that the long-term care policy in an aged society needs to take into account the increasing high prevalence of dementia in the institution.

Photoplethysmography (PPG) is well suited for wearable health applications, but has a lower frequency spectrum than electrocardiography (ECG) and is more affected by motion artifacts. In this study, ten signal filters from three categories were investigated in combination with different sampling rates to evaluate their effects on PPG signal quality. A correlation and accuracy analysis was performed comparing the interbeat intervals detected in PPG and ECG using Pearson correlation and absolute error. The results showed that specific filters with sampling rates as low as 40 Hz perform well in detecting autonomic neuropathy. The results highlight the potential of PPG with optimized filters and sampling rates for clinical screening of the autonomic nervous system (ANS) in wearable health monitoring.