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BackgroundTranscatheter aortic valve implantation (TAVI) is a standard treatment for patients with aortic valve stenosis due to its very low mortality and complication rates. However, survival and physical integrity are not the only important factors. Quality of life (QoL) improvement is a crucial part in the evaluation of therapy success.MethodsPatients with TAVI were questioned about their QoL before, one month and one year after the intervention as part of the INTERVENT registry trial at Mainz University Medical Center. Three different questionnaires were included in the data collection (Katz ADL, EQ-5D-5l, PHQ-D).ResultsWe included 285 TAVI patients in the analysis (mean age 79.8 years, 59.4% male, mean EuroSCORE II 3.8%). 30-day mortality was 3.6%, complications of any kind occurred in 18.9% of the patients. Main finding was a significant increase in the general state of health measured on the visual analog scale by an average of 4.53 (± 23.58) points (BL to 1-month follow-up, p = 0.009) and by 5.19 (± 23.64) points (BL to 12-month follow-up, p = 0.016). There was also an improvement of depression symptoms, which was reflected in a decrease in the total value of the PHQ-D by 1.67 (± 4.75) points (BL to 12-month follow-up, p = 0.001). The evaluation of the EQ-5D-5l showed a significant improvement in mobility after one month (M = −0.41 (± 1.31), p

IntroductionDepression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature.MethodsThis paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK.Results and discussionThe framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings.

Background: Cardiovascular disease (CVD) is a complex disease resulting from multiscale risk factors including genetics, age, and psychosocial factors (PSFs) such as depression and social isolation. However, previous research has lacked in operationalizing multiscale risk factors to determine individual and interactive associations over the life course. Therefore, this study aimed to evaluate individual and interactive associations of multiscale risk factors for CVD outcomes including genetics and PSFs at middle and older-aged stages of the life course.Methods: Baseline data from the Canadian Longitudinal Study on Aging (CLSA; n = 9,892 with genome-wide genotyping data) was used for this investigation. A 39 single nucleotide polymorphism polygenic risk score (PRS) for CVD was constructed. PSFs consisted of: (1) Depressive symptoms categorized into: “none” (Group 1, reference), “current” (Group 2), “clinical depression with no current symptoms” (Group 3), and “potential, recurrent depression” (Group 4); and (2) Social isolation index as a binary variable comprised of marital status, living arrangements, retirement status, contacts, and social participation. Heart-related disorders (HRD: myocardial infarction, angina and heart disease) was the primary outcome of interest and peripheral/vascular-related disorders (PVRD: stroke, peripheral vascular disease and hypertension) was the secondary outcome. Multivariable logistic regression models adjusted for socio-demographic factors were conducted stratified by age group (middle-aged: 45–69 years, older-aged: ≥70 years).Results: PRS was associated with HRD among middle- and older-aged participants [OR (95% confidence interval)] [1.06 (1.03–1.08), 1.06 (1.03–1.08), respectively]. Most depressive symptoms groups compared to the reference associated with HRD and PVRD, but only Group 4 associated with PVRD among older-aged [1.69 (1.08–2.64)]. Social isolation was associated with only PVRD among middle-aged [1.84 (1.04–3.26)]; however, socially isolated CLSA participants were underrepresented in the genotyped cohort (1.2%). No significant PRS*PSFs interactions were observed.Conclusions: Genetics and PSFs are independently associated with CVD. Varying observations across age groups underscores the need to advance research on multiscale risk factors operating both at a given point in time and over the life course. Future cohort studies may benefit from use of mobile assessment units to enable better reach to socially isolated participants for collection of biospecimens.

Major depressive disorders are global health problems that affect more than 6% of the U.S. population. Despite years of research, the etiology of depression remains unclear. Historically, it was believed that depression started within the central nervous system (CNS), but alternative hypotheses have recently challenged this dogma. Indeed, experimental and clinical evidence show that the gut microbiome could be an active player in depression initiation. The composition of bacterial species in depressed patients is significantly different from control microbiomes, and the transfer of the microbiome from depressed patients is sufficient to initiate depressive symptoms in animals. Additionally, the gut microbiome is known to change in the presence of depression risk factors such as chronic stress. While there is strong evidence delineating a role for microbial dysbiosis in depression, the initiating event for this dysbiosis remains unknown. Within the gut, microbiota reside in the mucus layer, a critical gel-like barrier involved in protecting the host from unwanted pathogen interactions, as well as regulating the immune system. Though the mucus layer is often ignored in the face of dysbiosis, it represents a dynamic and important piece of host machinery that has the potential to impact a wide variety of biological processes. Here, we review evidence supporting the novel concept that stress can modify the delicate mucus-microbiome balance, initiating dysbiosis, and ultimately leading to depression.

Major depressive disorders are global health problems that affect more than 6% of the U.S. population. Despite years of research, the etiology of depression remains unclear. Historically, it was believed that depression started within the central nervous system (CNS), but alternative hypotheses have recently challenged this dogma. Indeed, experimental and clinical evidence show that the gut microbiome could be an active player in depression initiation. The composition of bacterial species in depressed patients is significantly different from control microbiomes, and the transfer of the microbiome from depressed patients is sufficient to initiate depressive symptoms in animals. Additionally, the gut microbiome is known to change in the presence of depression risk factors such as chronic stress. While there is strong evidence delineating a role for microbial dysbiosis in depression, the initiating event for this dysbiosis remains unknown. Within the gut, microbiota reside in the mucus layer, a critical gel-like barrier involved in protecting the host from unwanted pathogen interactions, as well as regulating the immune system. Though the mucus layer is often ignored in the face of dysbiosis, it represents a dynamic and important piece of host machinery that has the potential to impact a wide variety of biological processes. Here, we review evidence supporting the novel concept that stress can modify the delicate mucus-microbiome balance, initiating dysbiosis, and ultimately leading to depression. [ABSTRACT FROM AUTHOR]