Objective: Chronic kidney disease (CKD) is often a multimorbid condition and progression to more severe disease is commonly associated with increased management requirements, including lifestyle change, more medication and greater clinician involvement. This study explored patients' and kidney care team's perspectives of the nature and extent of this workload (treatment burden) and factors that support capacity (the ability to manage health) for older individuals with CKD.
Design: Qualitative semistructured interview and focus group study.
Setting And Participants: Adults (aged 60+) with predialysis CKD stages G3-5 (identified in two general practitioner surgeries and two renal clinics) and a multiprofessional secondary kidney care team in the UK.
Results: 29 individuals and 10 kidney team members were recruited. Treatment burden themes were: (1) understanding CKD, its treatment and consequences, (2) adhering to treatments and management and (3) interacting with others (eg, clinicians) in the management of CKD. Capacity themes were: (1) personal attributes (eg, optimism, pragmatism), (2) support network (family/friends, service providers), (3) financial capacity, environment (eg, geographical distance to unit) and life responsibilities (eg, caring for others). Patients reported poor provision of CKD information and lack of choice in treatment, whereas kidney care team members discussed health literacy issues. Patients reported having to withdraw from social activities and loss of employment due to CKD, which further impacted their capacity.
Conclusion: Improved understanding of and measures to reduce the treatment burden (eg, clear information, simplified medication, joined up care, free parking) associated with CKD in individuals as well as assessment of their capacity and interventions to improve capacity (social care, psychological support) will likely improve patient experience and their engagement with kidney care services.
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http://dx.doi.org/10.1136/bmjopen-2020-042548 | DOI Listing |
J Intern Med
December 2024
Fresenius Medical Care, Global Medical Office, Bad Homburg, Germany.
Background: Fluid overload remains critical in managing patients with end-stage kidney disease. However, there is limited empirical understanding of fluid overload's impact on mortality. This study analyzes fluid overload trajectories and their association with mortality in hemodialysis patients.
View Article and Find Full Text PDFBMJ Open
December 2024
School of Medicine, Keele University, Keele, UK.
Objective: The proportion of people having home dialysis for kidney disease varies considerably by treating centre, socioeconomic deprivation levels in the area and to some extent ethnicity. This study aimed to gain in-depth insights into cultural and organisational factors contributing to this variation in uptake.
Design: This is the first ethnographic study of kidney centre culture to focus on home dialysis uptake.
Transpl Immunol
December 2024
Pulmonary, Critical Care and Cardiothoracic Surgery, Northwell Health Systems, 300 Community Dr, Manhasset, NY 11030, United States of America.
Introduction: Tacrolimus-induced thrombotic microangiopathy (TMA) causing acute kidney injury (AKI) without systemic features is a rare entity, particularly after non-renal solid organ transplantation.
Case Report: We describe the case of a patient with AKI after combined heart and lung transplantation. Renal biopsy revealed acute thrombotic microangiopathy which ultimately prompted initiation of eculizumab, a monoclonal antibody targeted against complement C5, with subsequent recovery in renal function.
Int Urol Nephrol
December 2024
Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
Purpose: With the increasing demand for dialysis, there is a growing emphasis on patient-centered care. This study investigated patients' satisfaction levels with peritoneal dialysis (PD) and hemodialysis (HD) care in Iran.
Methods: A cross-sectional multicenter study was conducted among 346 patients with chronic kidney disease (CKD) covered by the Iran Health Insurance Organization who received dialysis services from October to December 2022 across the country.
J Am Med Inform Assoc
December 2024
AI for Health Institute, Washington University in St Louis, St Louis, MO 63130, United States.
Objective: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the effectiveness of predicting postoperative complications using a novel surgical Variational Autoencoder (surgVAE) that uncovers intrinsic patterns via cross-task and cross-cohort presentation learning.
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