Cognitive Impairment and Cardiovascular Disease in Older Adults: An Evaluation Using Pooled Observational Data
Author(s)
Zaidi SH1, Chen S2, Maibach J2, White L2, LaFleur B3
1University of Arizona, Tucson, AZ, USA, 2University of Arizona BIO5 Institute, Tucson, AZ, USA, 3Center for Health Outcomes & PharmacoEconomic Research (HOPE Center), Tucson, AZ, USA
Presentation Documents
OBJECTIVES: There have been several studies examining the coexistence of cardiovascular disease and cognitive impairment in older adults. However, there have been conflicting literature, particularly around timing and severity of cardiac events (e.g., antecedent) and mild cognitive impairment (MCI). Some of these studies are limited by the nature of cognitive function testing in standard of care follow-up. Given these challenges we examine effect of CVD risk factors and modification of these risk factors and cognitive impairment in three observational studies that have harmonized data collection protocols.
METHODS: Data will be analyzed from three observational studies: The Alzheimer’s Disease Neuroimaging Initiative (ADNI); National Alzheimer’s Coordinating Center (NACC); and The Australian Imaging, Biomarker and Lifestyle (AIBL) study. These studies capture clinical diagnosis of MCI as well as the history and follow-up information for CVD diagnoses. Additionally, these studies also track information regarding CVD treatment, which some researchers have suggested might be an important prevention strategy, particularly for modifiable MCI. Using a pooled data approach that weighs each study by the sample size available after harmonization of variables, we examine the timing of diagnosis of CVD and clinical diagnosis of MCI, adjusted for CVD controlling medication use. Additionally, we will use a hidden Markov model to evaluate whether the MCI diagnosis is sustained or potentially modifiable by CVD treatment.
RESULTS: Results from a multivariable logistic regression in only the NACC data found CVD history to be highly significant covariate of MCI transition (chi-squared p-value of 0.0002) and those with a history of CVD and on medication showed lower rates of MCI transition.
CONCLUSIONS: While early findings underscore the importance of complex interaction between CVD and cognitive impairment, a pooled data approach and application of hidden Markov model will provide a more nuanced understanding of complex interplay between CVD and MCI transition.
Conference/Value in Health Info
Value in Health, Volume 27, Issue 6, S1 (June 2024)
Code
SA42
Topic
Study Approaches
Topic Subcategory
Decision Modeling & Simulation, Literature Review & Synthesis, Prospective Observational Studies
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), Neurological Disorders