1,720,998 research outputs found
Cardioprotective effects of glucagon-like peptide 1 receptor agonists in heart failure: Myth or truth?
No full text: Therapy with glucagon-like peptide 1 (GLP1) receptor agonists has raised great interest for its beneficial cardiovascular effects in preventing atherosclerosis and heart failure-related outcomes. However, while evidence about atherosclerosis consistently suggests a cardioprotective potential with class effect, controversies remain on its impact on heart failure. GLP1 receptor agonists appear to prevent hospitalization for new-onset heart failure and reduce symptoms in heart failure with preserved ejection fraction (as demonstrated by the recent STEP-HFpEF Trial). Still, GLP1 agonism has resulted in neutral or even harmful effects in patients with established heart failure with reduced ejection fraction (the LIVE trial). GLP1 receptor agonists benefit the cardiovascular system indirectly through their marked metabolic effects (improved weight management, glycemic control, blood pressure, systemic and tissue inflammation), while direct effects on the heart have been questioned. Nonetheless, weight loss alone achieved through GLP1 receptor agonists has failed in improving left ventricular functions. Tirzepatide is a dual agonist of GLP1 and glucose-dependent insulinotropic polypeptide, representing an innovative treatment option in diabetes with a major impact on weight loss and promising cardiovascular benefits. Whether this class of therapies is going to change the history of heart failure is an ongoing debate
Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data
Full text link: The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur in multichronic patients. We analyse data from a large adult population of multichronic patients living in Tuscany (Italy) in 2019 which was stratified by sex and age classes. Results demonstrate that (i) cardio-metabolic, endocrine, and neuro-degenerative diseases represent a stable pattern of multimorbidity, and (ii) disease prevalence and clustering vary across ages and between women and men. Identifying the most common multichronic profiles can help tailor medical protocols to patients' needs and reduce costs. Furthermore, analysing temporal patterns of disease can refine risk predictions for evolutive chronic conditions
Manipulating the Sequence of Nutrient Ingestion Improves Real-Life Glycemic Control in Type 2 Diabetes
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Endocrine and haemodynamic stress responses to an arithmetic cognitive challenge
No full textWe aimed at developing and validating a simple, highly repeatable computer-based tool, which could be employed to simulate the effects of an acute mental stress on endocrine and haemodynamic stress responses
Rare Variants in Melanocortin 4 Receptor Gene (MC4R) Are Associated with Increased Visceral Fat and Altered Glucose Metabolism Independent of the Effect of Obesity in Children
No full textMelanocortin 4 receptor gene (MC4R) mutations result in early-onset obesity, but it is unclear how they affect abdominal fat distribution, intrahepatic fat, and related metabolic sequelae. 484 overweight/obese (BMI >85th percentile for age, sex, and height) youth (6-21 years) were screened for functionally damaging, rare variants (minor allele frequency <0.01) in the coding region of MC4R and were assigned to a Pathogenic Variant (n=10) or No Variant (n=474) group. Participants underwent MC4R sequencing, abdominal MRI, and a 180-minute oral glucose tolerance test (OGTT) with mathematical modeling of insulin kinetics and β cell function. Compared to No Variant group, the Pathogenic Variant group showed greater visceral fat (Figure 1A) , intrahepatic fat (Figure 1B) , and higher plasma glucose (Figure 1C) and insulin (Figure 1D) during the OGTT, as well as a delayed glucose peak (65.4 ± 3.71 vs. 58.8 ± 0.417 minutes; P=0.036) , insulin resistance (WBISI: 0.9± 0.163 vs. 1.82 ± 0.051; P=0.0006) , and lower insulin clearance (0.441 ± 0.065 vs. 0.6± 0.012 μU/mL/min; P=0.033) despite similar BMI z-scores (P=0.189) and body fat percentage (P=0.704) between groups. These results show that rare variants in MC4R are associated with increased visceral fat, intrahepatic fat, and insulin resistance, independent from the effect of obesity
Predictive Role of Atherosclerosis Biomarkers on Carotid Plaque Extension in Type 2 Diabetes
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Ethnicity and Common Genetic Variants Modulate Nonalcoholic Fatty Liver Disease (NAFLD) Metabolic Phenotype in Obese Youth
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