Background: Perceptions of families who take care of patients suffering from advanced illness are rarely considered in Kinshasa medical practices; nevertheless, these families are the main actors involved in such care. The objective of this present study was to illustrate, in a Congolese context, the perceptions of families on the care of patients suffering from advanced illness, and to identify the possible aids provided by healthcare facilities.
Methods: A qualitative study was performed among focus groups in six hospitals in Kinshasa. Each group included eight members.
Results: We gathered factors that could negatively influence the care of a patient suffering from advanced disease. Such factors included: scarcity of and inaccessibility to painkillers, economic resilience, poor quality treatment, lack of psychological counselling, seeking alternative solutions and poor communication between caregivers and patients. In contrast, the study also showed that relatives caring for these patients often receive support from the wider family and from cult members.
Conclusions: This study focuses on the miscommunication between healthcare workers and patients, poor management in advanced illness as well as a lack of psychological support from caregivers. The findings can serve as basis for further research in palliative care.
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http://dx.doi.org/10.21037/apm.2017.03.13 | DOI Listing |
Malays J Pathol
December 2024
Universiti Kebangsaan Malaysia, 43600 Bangi, Faculty of Medicine, Department of Pharmacology, 56000 Cheras, Kuala Lumpur, Malaysia.
Osteoarthritis (OA) is a prevalent degenerative joint disease characterised by cartilage and subchondral bone breakdown, impacting millions worldwide. This review provides an overview of the complex aetiology of OA, integrating biochemical, mechanical, and genetic factors. It also emphasises a multifaceted management approach, combining non-pharmacological, pharmacological, and surgical treatments.
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February 2025
Department of Anaesthesiology and Perioperative Medicine, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
Background: Lung cancer surgery is associated with a high incidence of chronic postsurgical pain (CPSP), which necessitates long-term analgesic prescriptions. However, while essential for managing pain, these have shown various adverse effects. Current guidelines recommend using peripheral nerve blocks over epidural anaesthesia for perioperative analgesia in minimally invasive thoracic surgery (MITS).
View Article and Find Full Text PDFHistopathology
December 2024
Goethe University Frankfurt, Medical Clinic 1, University Hospital, Frankfurt am Main, Germany.
Aims: Anti-claudin-18.2 (CLDN18.2) therapy was recently approved for the treatment of gastric or gastro-oesophageal junction adenocarcinoma.
View Article and Find Full Text PDFAnn Surg Oncol
December 2024
Department of Thoracic Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Background: Immunochemotherapy is inevitably accompanied with treatment-related adverse events (TRAEs). However, TRAEs are typically assessed at a single time point, overlooking the complexity of TRAE trajectories over time. This study aimed to characterize TRAE trajectories during multi-cycle neoadjuvant immunochemotherapy (nICT) and identify potential prognostic factors for patients with esophageal squamous cell carcinoma (ESCC).
View Article and Find Full Text PDFCommun Biol
December 2024
College of Computer Science and Technology, Ocean University of China, Qingdao, China.
Understanding the function of proteins is of great significance for revealing disease pathogenesis and discovering new targets. Benefiting from the explosive growth of the protein universal, deep learning has been applied to accelerate the protein annotation cycle from different biological modalities. However, most existing deep learning-based methods not only fail to effectively fuse different biological modalities, resulting in low-quality protein representations, but also suffer from the convergence of suboptimal solution caused by sparse label representations.
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