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[Clinical characteristics and pharmacological treatment of patients with heart failure in a primary health care cohort].

Aten Primaria

January 2025

Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, España; Department of Pharmacology, Therapeutics and Toxicology, Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Barcelona, España; Institut Català de la Salut, Barcelona, España.

Objective: To characterise patients with heart failure (HF) in Primary Health Care (PHC) and describe their socio-demographic and clinical characteristics and pharmacological treatment.

Design: Descriptive cohort study. SITE: Information System for the Development of Research in Primary Care (SIDIAP), which captures information from the electronic health records of PHC of the Catalan Institute of Health (approximately 80% of the Catalan population).

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Background: Non-communicable diseases (NCDs) are governed by a cluster of unhealthy behaviours and their determinants, like tobacco and alcohol, unhealthy diet, lack of physical activity, overweight and obesity, pollution (air, water, and soil), and stress. Regulation of these unhealthy behaviours plays a crucial role in blood pressure control among individuals on hypertensive treatment, especially those suffering from uncontrolled hypertension. Hence, the present study aims at identifying the unhealthy behaviours associated with uncontrolled hypertension.

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Nanocarriers have shown significant promise in the diagnosis and treatment of various diseases, utilizing a wide range of biocompatible materials such as metals, inorganic substances, and organic components. Despite diverse design strategies, key physicochemical properties, including hydrodynamic diameter, shape, surface charge, and hydrophilicity/lipophilicity, are crucial for optimizing biodistribution, pharmacokinetics, and therapeutic efficacy. However, these properties are often influenced by drug payload, presenting an ongoing challenge in developing versatile platform technologies for theranostics.

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This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of improving the diagnosis and treatment of coronary artery disease. The methodology included data collection in a clinical environment, followed by data preparation and analysis using the 3D Slicer Platform for manual segmentation, and subsequently, the application of artificial intelligence models for automated segmentation, focusing on the efficiency of identifying the walls of the left ventricular. A total of 83 clinical routine exams were collected, each exam containing 50 slices, which is 4,150 images.

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Peru is among Latin American countries with the largest Indigenous population, yet ethnical health disparities persist, particularly in the Amazon region which comprises 60% of the national territory. Healthcare models that include Indigenous medicine and traditional healers present an important avenue for addressing such inequalities, as they increase cultural adequacy of services, healthcare access, and acknowledge Indigenous Rights for their perspectives to be represented in public healthcare. Understanding the underlying epistemologies of Indigenous medicine is a prerequisite for this purpose.

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