Heart failure (HF) and renal dysfunction often coexist and interact in many complex and bidirectional pathways, leading to detrimental effects on patient outcomes. The treatment of HF patients with renal dysfunction presents a significant clinical challenge. Interestingly, sacubitril/valsartan, an angiotensin receptor-neprilysin inhibitor (ARNI), may have beneficial effects on cardiac and renal outcomes in patients with HF with reduced ejection fraction, particularly by slowing the rate of decrease in the estimated glomerular filtration rate compared to a single angiotensin-converting enzyme inhibitor. Recently, more reports have emphasized the renal protection of sacubitril/valsartan in patients with HF. In HF patients with renal dysfunction, however, there is no strong evidence supporting the use of sacubitril/valsartan to reduce the absolute risk of hyperkalemia and worsening renal function; therefore, the administration of ARNI requires a careful balance between the benefits and risks. Furthermore, the lack of evidence-based management highlights the importance of an individualized approach based on published experience and multidisciplinary collaborations, as well as underlines the need for in-depth studies investigating the underlying mechanisms in cardiorenal interactions with a focus on treatments.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11554417 | PMC |
http://dx.doi.org/10.1155/2024/6231184 | DOI Listing |
CNS Neurosci Ther
January 2025
Department of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Objective: This study investigates the association between blood urea nitrogen (BUN) levels and the risk of delirium in critically ill elderly patients without kidney disease.
Methods: A retrospective analysis was conducted using data from the MIMIC-IV database. The relationship between BUN and delirium risk was illustrated through the restricted cubic spline (RCS) method.
Neurol Ther
January 2025
Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome, Italy.
Hereditary transthyretin amyloidosis (ATTRv, v for variant) is a genetic disorder characterized by the deposition of misfolded transthyretin (TTR) protein in tissues, resulting in progressive dysfunction of multiple organs, including the nervous system, heart, kidneys, and gastrointestinal (GI) tract. Noninvasive serum biomarkers have become key tools for diagnosing and monitoring ATTRv. This review examines the role of available biomarkers for neurological, cardiac, renal, gastrointestinal, and multisystemic involvement in ATTRv.
View Article and Find Full Text PDFEcotoxicol Environ Saf
January 2025
National Key Laboratory of Veterinary Public Health Security, College of Veterinary Medicine, China Agricultural University, Haidian, Beijing 100193, China. Electronic address:
Obesity is a contributing factor that increases the likelihood of developing chronic kidney disease. In recent years, studies have found that light pollution worldwide promoted obesity, which was known to be a consequence of circadian rhythm disruption. Nevertheless, the impact of light pollution on kidney disease associated with obesity remains mostly unknown, and potential processes have been minimally investigated.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha, China.
Background: Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and health care costs. Major adverse kidney events within 30 days (MAKE30), a composite of death, new renal replacement therapy, or persistent renal dysfunction, has been recommended as a patient-centered endpoint for clinical trials involving AKI.
Objective: This study aimed to develop and validate a machine learning-based model to predict MAKE30 in hospitalized older patients with AKI.
PLoS One
January 2025
Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Müunster, Müunster, Germany.
Objective: Acute kidney injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria to time series, requires researchers to implement classification algorithms of their own which is resource intensive and might impact study quality by introducing different interpretations of edge cases. This project introduces pyAKI, an open-source pipeline addressing this gap by providing a comprehensive solution for consistent KDIGO criteria implementation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!