Healthcare systems in low-income and lower-middle income countries (LLMICs) face significant challenges in the provision of health services, for example, kidney care to the population. Although this is linked to several high-level factors such as poor infrastructure, socio-demographic and political factors, healthcare funding has often been cited as the major reason for the wide gap in availability, accessibility and quality of care between LLMICs and rich countries. With the steady rising incidence and prevalence of kidney diseases globally, as well as cost of care, LLMICs are likely to suffer more consequences of these increases than rich countries and may be unable to meet targets of universal health coverage (UHC) for kidney diseases. As health systems in LLMICs continue to adapt in finding ways to provide access to affordable kidney care, various empirical and evidence-based strategies can be applied to assist them. This review uses a framework for healthcare strengthening developed by the World Health Organization (WHO) to assess various challenges that health systems in LLMICs confront in providing optimal kidney care to their population. We also suggest ways to overcome these barriers and strengthen health systems to improve kidney care in LLMICs.
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http://dx.doi.org/10.1111/nep.13935 | DOI Listing |
Infect Disord Drug Targets
January 2025
HCA Healthcare Las Palmas/Del Sol Internal Medicine Program.
Background: Streptococcal Toxic Shock Syndrome (STSS) is a life-threatening condition caused by bacterial toxins. The STSS triad encompasses high fever, hypotensive shock, and a "sunburn-like" rash with desquamation. STSS, like Toxic Shock Syndrome (TSS), is a rare complication of streptococcal infec-tions caused by Group A Streptococcus (GAS), Streptococcal pyogenes (S.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Immunology, University Hospital Zurich (USZ), Zurich, Switzerland.
Background: Donor-derived cell-free DNA (dd-cfDNA) is a promising non-invasive biomarker for detecting graft injury in solid organ transplant recipients. Elevated dd-cfDNA levels are strongly associated with rejection and graft injury, especially antibody-mediated rejection (ABMR). While donor-specific antibodies (dnDSA) are crucial in ABMR, the relationship between dd-cfDNA levels and dnDSA features, such as DSA category, MFI and HLA target loci, remains unclear.
View Article and Find Full Text PDFSci Prog
January 2025
Critical Care Medicine, Fortis Hospital Bannerghatta road, Bengaluru, Karnataka, India.
Objective: To study the impact of kinetic glomerular filtration rate (kGFR) on clinical decision making and its implications on drug dosing compared to that of estimated GFR (eGFR) using chronic kidney disease epidemiology collaboration (CKD-EPI) equation in critically ill patients with acute kidney injury (AKI) admitted in a tertiary level intensive care unit (ICU).
Methods: Cross-sectional, prospective, observational study design. All patients admitted to Medical ICU, Fortis Hospital, Bangalore with AKI defined as per AKI network (AKIN) criteria.
BMC Pregnancy Childbirth
January 2025
Department of Intensive Care Medicine, Army Medical Center of PLA, No. 10 Changjiang Road, Yuzhong District, Chongqing, 400010, People's Republic of China.
Background: Pregnancy-associated atypical hemolytic uremic syndrome (aHUS) is a form of thrombotic microangiopathy (TMA) caused by uncontrolled activation of the complement system during pregnancy or the postpartum period. In the intensive care unit, aHUS must be differentiated from sepsis-related multiple organ dysfunction, thrombotic thrombocytopenic purpura (TTP), hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome. Early recognition of aHUS is critical for effective treatment and improved prognosis.
View Article and Find Full Text PDFBMC Nephrol
January 2025
Department of Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman, Liège, Belgium.
Background: Creatinine-based estimated glomerular filtration rate (eGFR) equations are widely used in clinical practice but exhibit inherent limitations. On the other side, measuring GFR is time consuming and not available in routine clinical practice. We developed and validated machine learning models to assess the trustworthiness (i.
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