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- Creators: Barrett, The Honors College
Methods: Male Sprague-Dawley rats were fed a chow diet or a high fat diet (HFD) for ten weeks. Endothelium-dependent vasodilation was measured in isolated mesenteric arterioles that were treated with or without 80 µg/ml sumac in the superfusate throughout the experiment.
Results: Sumac did not improve vasodilation or in ex vivo arteries from rats fed a high fat diet. There were trends of improved vasodilation in sumac treated vessels from high fat diet rats, but sumac did not significantly improve vasodilation. In rats fed a chow diet, sumac prevented phenylephrine (PE) constriction in the vascular tissue. The most likely cause for this is the presence of Gallic acid in sumac. Another possible explanation is the presence of nitrates in sumac which may have prevented PE vasoconstriction.
Conclusions: Sumac did not significantly improve vasodilation in isolated arteries from rats fed a high fat diet. The results are inconclusive for the improvement of symptoms or risk of vascular dementia. In vivo treatment with sumac should be tested as results may differ.
DESIGN: Patient charts were reviewed to obtain demographic information, medications, and patients' progress throughout stay including pharmacologic and non-pharmacologic interventions and results. Patients were then interviewed using the short portable mental status questionnaire.
SETTING: The prevalence and management of dementia and delirium was evaluated in 10 Hospice of the Valley inpatient settings.
RESULTS: Out of the 159 participants (mean age = 77.72 years), 93 (58.5%) presented with moderate to severe cognitive impairment, but only 38 participants (23.9%) had a formal diagnosis of dementia. Out of the 93 participants with significant cognitive impairment, 60 participants (65.6%) were treated with benzodiazepines and 82 (88.2%) were treated with opioids. Fifty-nine (63.4%) participants with cognitive impairment had documented non pharmacological interventions such as repositioning and reorientation, but only 22 (23.7%) participants received more meaningful non-pharmacological interventions such as hand massages, targeted videos, and favorite music.
CONCLUSIONS: The current study found a high prevalence of moderate to severe cognitive impairment without a diagnosis of dementia. A likely cause is the high frequency of opioids and benzodiazepines prescribed, causing drug-induced sedation and delirium which significantly impairs cognitive abilities. Safer alternatives, such as non-opioid pain medications, should be considered within the hospice population, especially given that age is a risk factor for delirium. A tool would be helpful to encourage staff to identify and document use of non-pharmacological interventions.
For those living lives devoted to taking care of others, it can be difficult to remember to take care of themselves. This thesis project is a review of quantitative and qualitative literature pertaining to self-care for the caregivers of Alzheimer's and dementia patients. Three nursing diagnoses and related nursing interventions were created using data from the evidence-based literature. With the proper knowledge and assistance, caregivers can better prepare for the future and participate in health-promoting self-care activities which may improve their quality of life.
Inflammatory genes are known to only show in African Americans and non-Hispanic Whites. The objective of this study was to observe the correlation from the obtained data of the prevalence of the APOE ε4 genotype. We examined cerebral free-water, a marker of neuroinflammation, hippocampal volume, and volume of white-matter hyperintensities in African Americans (AA) and non-Hispanic Whites who were categorized in groups based on whether they had APOE ε4 allele or not. AA had lower prevalence of APOE e4 genotype than non-Hispanic Whites. AA groups have a slightly higher hippocampal volume compared to the Non-Hispanic White (NHW) groups. African Americans also reported increased white-matter hyperintensities and cerebral free-water. Hippocampal atrophy is associated with Alzheimer's disease, this might suggest that the AA groups have a lower risk of Alzheimer's, although further research is needed to confirm this relationship. Lastly, our findings also suggest other potential socioeconomic factors that could contribute to increased incidence of dementia among AA and potential resilience factors early in the course of Alzheimer’s disease process.
The burden of dementia and its primary cause, Alzheimer’s disease, continue to devastate many with no available cure although present research has delivered methods for risk calculation and models of disease development that promote preventative strategies. Presently Alzheimer’s disease affects 1 in 9 people aged 65 and older amounting to a total annual healthcare cost in 2023 in the United States of $345 billion between Alzheimer’s disease and other dementias making dementia one of the costliest conditions to society (“2023 Alzheimer’s Disease Facts and Figures,” 2023). This substantial cost can be dramatically lowered in addition to a reduction in the overall burden of dementia through the help of risk prediction models, but there is still a need for models to deliver an individual’s predicted time of onset that supplements risk prediction in hopes of improving preventative care. The aim of this study is to develop a model used to predict the age of onset for all-cause dementias and Alzheimer’s disease using demographic, comorbidity, and genetic data from a cohort sample. This study creates multiple regression models with methods of ordinary least squares (OLS) and least absolute shrinkage and selection operator (LASSO) regression methods to understand the capacity of predictor variables that estimate age of onset for all-cause dementia and Alzheimer’s disease. This study is unique in its use of a diverse cohort containing 346 participants to create a predictive model that originates from the All of Us Research Program database and seeks to represent an accurate sampling of the United States population. The regression models generated had no predictive capacity for the age of onset but outline a simplified approach for integrating public health data into a predictive model. The results from the generated models suggest a need for continued research linking risk factors that estimate time of onset.