Background: Acute kidney injury (AKI) is common among hospitalized patients with COVID-19 and associated with worse prognosis. The Spanish Society of Nephrology created the AKI- COVID Registry to characterize the population admitted for COVID-19 that developed AKI in Spanish hospitals. The need of renal replacement therapy (RRT) therapeutic modalities, and mortality in these patients were assessed MATERIAL AND METHOD: In a retrospective study, we analyzed data from the AKI-COVID Registry, which included patients hospitalized in 30 Spanish hospitals from May 2020 to November 2021. Clinical and demographic variables, factors related to the severity of COVID-19 and AKI, and survival data were recorded. A multivariate regression analysis was performed to study factors related to RRT and mortality.
Results: Data from 730 patients were recorded. A total of 71.9% were men, with a mean age of 70 years (60-78), 70.1% were hypertensive, 32.9% diabetic, 33.3% with cardiovascular disease and 23.9% had some degree of chronic kidney disease (CKD). Pneumonia was diagnosed in 94.6%, requiring ventilatory support in 54.2% and admission to the ICU in 44.1% of cases. The median time from the onset of COVID-19 symptoms to the appearance of AKI (37.1% KDIGO I, 18.3% KDIGO II, 44.6% KDIGO III) was 6 days (4-10). A total of 235 (33.9%) patients required RRT: 155 patients with continuous renal replacement therapy, 89 alternate-day dialysis, 36 daily dialysis, 24 extended hemodialysis and 17 patients with hemodiafiltration. Smoking habit (OR 3.41), ventilatory support (OR 20.2), maximum creatinine value (OR 2.41), and time to AKI onset (OR 1.13) were predictors of the need for RRT; age was a protective factor (0.95). The group without RRT was characterized by older age, less severe AKI, and shorter kidney injury onset and recovery time (p < 0.05). 38.6% of patients died during hospitalization; serious AKI and RRT were more frequent in the death group. In the multivariate analysis, age (OR 1.03), previous chronic kidney disease (OR 2.21), development of pneumonia (OR 2.89), ventilatory support (OR 3.34) and RRT (OR 2.28) were predictors of mortality while chronic treatment with ARBs was identified as a protective factor (OR 0.55).
Conclusions: Patients with AKI during hospitalization for COVID-19 had a high mean age, comorbidities and severe infection. We defined two different clinical patterns: an AKI of early onset, in older patients that resolves in a few days without the need for RRT; and another more severe pattern, with greater need for RRT, and late onset, which was related to greater severity of the infectious disease. The severity of the infection, age and the presence of CKD prior to admission were identified as a risk factors for mortality in these patients. In addition chronic treatment with ARBs was identified as a protective factor for mortality.
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http://dx.doi.org/10.1016/j.nefroe.2023.03.017 | DOI Listing |
J 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.
Diabetes
January 2025
Centre de recherche, Centre hospitalier de l'Université de Montréal (CRCHUM) and Département de médecine, Université de Montréal, 900 Saint Denis Street, Montréal, QC Canada H2X 0A9.
The role of the intrarenal renin-angiotensin system (iRAS) in diabetic kidney disease (DKD) progression remains unclear. In this study, we generated mice with renal tubule-specific deletion of angiotensinogen (Agt; RT-Agt-/-) in both Akita and streptozotocin (STZ)-induced mouse model of diabetes. Both Akita RT-Agt-/- and STZ-RT-Agt-/- mice exhibited significant attenuation of glomerular hyperfiltration, urinary albumin/creatinine ratio, glomerulomegaly and tubular injury.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Institute of Optical Materials and Chemical Biology, Guangxi Key Laboratory of Electrochemical Energy Materials, School of Chemistry and Chemical Engineering, Guangxi University, Nanning 530004, Guangxi, People's Republic of China.
Monitoring subcellular organelle dynamics in real time and precisely assessing membrane heterogeneity in living cells are very important for studying fundamental biological mechanisms and gaining a comprehensive understanding of cellular processes. However, there remains a shortage of effective tools for these purposes. Herein, we propose a strategy to develop the exchangeable water-sensing probeAPBD for time-lapse imaging of dynamics in cellular membrane-bound organelle morphology with structured illumination microscopy at the nanoscale.
View Article and Find Full Text PDFPLoS 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 PDFIndian J Pediatr
January 2025
Department of Internal Medicine, Yanbian University Hospital, Yanji, Jilin, 133002, China.
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