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Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic., info:eu-repo/semantics/published

BackgroundClinical Dementia Rating Sum of Boxes (CDRSOB) scale is known to be highly indicative of cognitive-functional status, but it is unclear whether it is consistent with clinician diagnosis in evaluating drug class associations with risk of progression to mild cognitive impairment (MCI) and dementia. MethodsWe employed multivariate logistic regression on longitudinal NACC data, to identify drug classes associated with disease progression risk, using clinician diagnosis and CDRSOB as the outcome. ResultsNon-steroidal anti-inflammatory drugs, anxiolytics, antidiabetics, and Parkinsons medications were significantly associated with decreased progression to mild cognitive impairment (MCI)/dementia, and antihypertensives and Alzheimers medications significantly associated with increased progression risk. Associations were however dependant on the diagnostic measure used, e.g., antihypertensives were associated with increased Healthy-to-Dementia risk using clinical diagnosis as the outcome (OR:2.05, FDR p

The increasing prevalence of dementia in older adults warrants attention to the identification of practices that can delay or reduce likelihood of progression to early forms of cognitive impairment, in particular, to mild cognitive impairment (MCI) which is often considered a transitional stage between healthy aging and dementia. In this study, we investigated the effect of hearing impairment and hearing aid usage on cognitive decline and progression to MCI in cognitively healthy individuals. We used data from a large referral-based cohort obtained from the National Alzheimer’s Coordinating Center. The baseline sample included 5721 cognitively normal subjects aged ≥ 40. We found that hearing impairment was associated with increased risk of progression to MCI (hazard ratio [HR] = 1.40, 95%CI, 1.16-1.68, false discovery rate [FDR] P < 0.001) and an accelerated rate of cognitive decline (P < 0.001). Among hearing-impaired participants, hearing aid users were less likely to develop MCI (HR, 0.33; 95% CI, 0.23-0.47; FDR P < 0.001) and experienced slower cognitive decline (P = 0.004) when compared to those not using hearing aids. We found no statistically significant differences in risk of conversion to MCI between individuals with normal hearing and hearing-impaired adults using hearing aids (HR, 1.23; 95% CI, 0.99-1.50; FDR P = 0.08). Our findings highlight the need for a randomized clinical trial that will allow us to investigate whether there is a causal relationship between hearing loss, hearing aid use, and conversion to MCI. Such knowledge could provide new and novel insights into prevention of cognitive impairment and dementia.

Introduction Conflicting results on dementia risk factors have been reported across studies. We hypothesize that variation in data preparation methods may partially contribute to this issue. Methods We propose a comprehensive data preparation approach comparing individuals with stable diagnosis over time to those who progress to mild cognitive impairment (MCI)/dementia. This was compared to the often‐used “baseline” analysis. Multivariate logistic regression was used to evaluate both methods. Results The results obtained from sensitivity analyses were consistent with those from our multi‐time‐point data preparation approach, exhibiting its robustness. Compared to analysis using only baseline data, the number of significant risk factors identified in progression analyses was substantially lower. Additionally, we found that moderate depression increased healthy‐to‐MCI/dementia risk, while hypertension reduced MCI‐to‐dementia risk. Discussion Overall, multi‐time‐point–based data preparation approaches may pave the way for a better understanding of dementia risk factors, and address some of the reproducibility issues in the field.