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Hypertension and Frailty Syndrome in Old Age

Abstract: Hypertension is both a health problem and a financial one globally. It affects nearly 30 % of the general population. Elderly people, aged ≥65 years, are a special group of hypertensive patients. In this group, the overall prevalence of the disease reaches 60 %, rising to 70 % in those aged ≥80 years. In the elderly population, isolated systolic hypertension is quite common. High systolic blood pressure is associated with an increased risk of cardiovascular disease, cerebrovascular disease, peripheral artery disease, cognitive impairment and kidney disease. Considering the physiological changes resulting from ageing alongside multiple comorbidities, treatment of hypertension in elderly patients poses a significant challenge to treatment teams. Progressive disability with regard to the activities of daily life, more frequent hospitalisations and low quality of life are often seen in elderly patients. There is discussion in the literature regarding frailty syndrome associated with old age. Frailty is understood to involve decreased resistance to stressors, depleted adaptive and physiological reserves of a number of organs, endocrine dysregulation and immune dysfunction. The primary dilemma concerning frailty is whether it should only be defined on the basis of physical factors, or whether psychological and social factors should also be included. Proper nutrition and motor rehabilitation should be prioritised in care for frail patients. The risk of orthostatic hypotension is a significant issue in elderly patients. It results from an autonomic nervous system dysfunction and involves maladjustment of the cardiovascular system to sudden changes in the position of the body. Other significant issues in elderly patients include polypharmacy, increased risk of falls and cognitive impairment. Chronic diseases, including hypertension, deteriorate baroreceptor function and result in irreversible changes in cerebral and coronary circulation. Concurrent frailty or other components of geriatric syndrome in elderly patients are associated with a worse perception of health, an increased number of comorbidities and social isolation of the patient. It may also interfere with treatment adherence. Identifying causes of non-adherence to pharmaceutical treatment is a key factor in planning therapeutic interventions aimed at increasing control, preventing complications, and improving long-term outcomes and any adverse effects of treatment. Diagnosis of frailty and awareness of the associated difficulties in adhering to treatment may allow targeting of those elderly patients who have a poorer prognosis or may be at risk of complications from untreated or undertreated hypertension, and for the planning of interventions to improve hypertension control.

The application of natural language processing for the extraction of mechanistic information in toxicology

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).

Cross cultural adaptation and validation of the 'Pátient-Generated Subjective Global Assessment (PG-SGA) for nutritional status of cancer patients in Iran

High prevalence of malnutrition and impact symptoms in older patients with cancer

The efficacy of oral and subcutaneous antigen-specific immunotherapy in murine cow's milk- and peanut allergy models

From Pubmed: " BACKGROUND: Antigen-specific immunotherapy (AIT) is a promising therapeutic approach for both cow's milk allergy (CMA) and peanut allergy (PNA), but needs optimization in terms of efficacy and safety. AIM: Compare oral immunotherapy (OIT) and subcutaneous immunotherapy (SCIT) in murine models for CMA and PNA and determine the dose of allergen needed to effectively modify parameters of allergy. METHODS: Female C3H/HeOuJ mice were sensitized intragastrically (i.g.) to whey or peanut extract with cholera toxin. Mice were treated orally (5 times/week) or subcutaneously (3 times/week) for three consecutive weeks. Hereafter, the acute allergic skin response, anaphylactic shock symptoms and body temperature were measured upon intradermal (i.d.) and intraperitoneal (i.p.) challenge, and mast cell degranulation was measured upon i.g. challenge. Allergen-specific IgE, IgG1 and IgG2a were measured in serum at different time points. Single cell suspensions derived from lymph organs were stimulated with allergen to induce cytokine production and T cell phenotypes were assessed using flow cytometry. RESULTS: Both OIT and SCIT decreased clinically related signs upon challenge in the CMA and PNA model. Interestingly, a rise in allergen-specific IgE was observed during immunotherapy, hereafter, treated mice were protected against the increase in IgE caused by allergen challenge. Allergen-specific IgG1 and IgG2a increased due to both types of AIT. In the CMA model, SCIT and OIT reduced the percentage of activated Th2 cells and increased the percentage of activated Th1 cells in the spleen. OIT increased the percentage of regulatory T cells (Tregs) and activated Th2 cells in the MLN. Th2 cytokines IL-5, IL-13 and IL-10 were reduced after OIT, but not after SCIT. In the PNA model, no differences were observed in percentages of T cell subsets. SCIT induced Th2 cytokines IL-5 and IL-10, whereas OIT had no effect. CONCLUSION: We have shown clinical protection against allergic manifestations after OIT and SCIT in a CMA and PNA model. Although similar allergen-specific antibody patterns were observed, differences in T cell and cytokine responses were shown. Whether these findings are related to a different mechanism of AIT in CMA and PNA needs to be elucidated."

Effectiveness and Outcome Moderators of Computer-Based Health Education for an Adult Population

This review of meta-analyses of outcome studies of adults receiving Computer-Based Health Education (CBHE) has two goals. The first is to provide an overview of the efficacy of CBHE interventions, and the second is to identify moderators of these effects. A systematic literature search resulted in 15 meta-analyses of 278 controlled outcome studies. The meta-analyses were analysed with regard to reported (overall) effect sizes, heterogeneity and interaction effects. The results indicate a positive relationship between CBHE interventions and improvements in health-related outcomes, with small overall effect sizes compared to non-computer-based interventions. The sustainability of the effects was observed for up to six months. Outcome moderators (31 variables) were studied in 12 meta-analyses and were clustered into three categories: intervention features (20 variables), participant characteristics (five variables) and study features (six variables). No relationship with effectiveness was found for four intervention features, theoretical background, use of internet and e-mail, intervention setting and self-monitoring; two participant features, age and gender; and one study feature, the type of analysis. Regarding the other 24 identified features, no consistent results were observed across meta-analyses. To enhance the effectiveness of CBHE interventions, moderators of effects should be studied as single constructs in high-quality study designs. http://www.journalofinterdisciplinarysciences.com/ https://www.linkedin.com/in/leontienvreeburg/