Objective: to understand the strengths and weaknesses in the care network of people with HIV/AIDS in a referral center in the state of Santa Catarina-SC.
Method: participants were eight subjects and their care network, totaling 18 participants. Data were collected through interviews and examined by content analysis, theoretically supported by symbolic interaction.
Results: the analysis resulted in the following categories: The network offering care to people with acquired immunodeficiency syndrome, and Facing Barriers in care, which reflect the strengths and weaknesses in the care network. The fi rst depicts the provision of emotional and humanized care, and the second a restricted network formed by health professionals and a family member.
Conclusion: the professional care network is important, despite the increased number of assistances in a physical structure and amount of professionals who no longer meet the growing demand.
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http://dx.doi.org/10.1590/0034-7167.2015680309i | DOI Listing |
Rheumatol Adv Pract
January 2025
Rheumatology Unit, ERN ReCONNET Center, IRCCS Meyer Children's Hospital, Firenze, Italy.
Objectives: Two different European Reference Networks cover CTDs with paediatric onset, the European Reference Network on Rare and Complex Connective Tissue Diseases (ERN ReCONNET) and the European Reference Network on Rare Immunological Disorders (ERN RITA). The transition of care is a significant focus, with ReCONNET centres actively addressing this through updated programs. Despite these efforts, challenges persist.
View Article and Find Full Text PDFArch Bone Jt Surg
January 2025
Orthopedic Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Sciences, Mashhad, Iran.
Artificial Intelligence (AI) is rapidly transforming healthcare, particularly in orthopedics, by enhancing diagnostic accuracy, surgical planning, and personalized treatment. This review explores current applications of AI in orthopedics, focusing on its contributions to diagnostics and surgical procedures. Key methodologies such as artificial neural networks (ANNs), convolutional neural networks (CNNs), support vector machines (SVMs), and ensemble learning have significantly improved diagnostic precision and patient care.
View Article and Find Full Text PDFJACC Adv
February 2025
Department of Cardiology, Barbra Streisand Women's Heart Center, Cedars Sinai- Smidt Heart Institute, Los Angeles, California, USA.
Background: Myocardial infarction (MI) poses a major financial burden on the U.S. health care system, but its impact on medical expenses and health care utilization when coupled with psychological distress remains unknown.
View Article and Find Full Text PDFChem Biomed Imaging
January 2025
Department of Radiology, Huaxi MR Research Center (HMRRC), Institution of Radiology and Medical Imaging and Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University. Chengdu 610041, Sichuan, China.
A variety of bioorthogonal chemical tools have been developed and widely used in the study of biological phenomena in situ. Tetrazine bioorthogonal chemistry exhibits ultrafast reaction kinetics, excellent biocompatibility, and precise optical regulatory capabilities. Fluorogenic tetrazine bioorthogonal probes have achieved particularly diverse applications in bioimaging and disease diagnosis and treatment.
View Article and Find Full Text PDFJACC Asia
January 2025
Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: Heart failure should be diagnosed as early as possible. Although deep learning models can predict one or more echocardiographic findings from electrocardiograms (ECGs), such analyses are not comprehensive.
Objectives: This study aimed to develop a deep learning model for comprehensive prediction of echocardiographic findings from ECGs.
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