Oliguric and non-oliguric acute renal failure was studied in a group of 28 high risk patients in an intensive care unit. Of these, 15 (53.5%) presented oliguric and 13 (46.4%) non oliguric acute renal failure. Causal agents of the renal failure were postoperative in 14 cases, mainly peritonitis; medical in 10 and posttraumatic in 4. Oliguric renal failure was most commonly medical, while non-oliguric renal failure was predominantly postoperative in origin (p less than 0.05). Results of urinalysis indicative of renal failure were similar in both groups: NAO, osmolarity, FeNa, BUN o/p and creatinine o/p, as were degree and course of renal failure, and the appearance of complications and indications for dialysis. There was no significant difference in mortality rate between oliguric (93%) and non-oliguric (85%) patients; total mortality was 89%. The results of this study clearly show that non-oliguric acute renal failure carries the same poor prognosis in high risk patients in intensive care units as do the oliguric forms of the entity.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Association between SOFA score and risk of acute kidney injury in patients with diabetic ketoacidosis: an analysis of the MIMIC-IV database.
Front Endocrinol (Lausanne)
December 2024
Department of Cardiovascular Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Introduction: The Sequential Organ Failure Assessment (SOFA) score is a widely utilized clinical tool for evaluating the severity of organ failure in critically ill patients and assessing their condition and prognosis in the intensive care unit (ICU). Research has demonstrated that higher SOFA scores are associated with poorer outcomes in these patients. However, the predictive value of the SOFA score for acute kidney injury (AKI), a common complication of diabetic ketoacidosis (DKA), remains uncertain.
View Article and Find Full Text PDFBackground: Alport syndrome (AS) is a multifaceted condition that primarily affects the basement membranes of the kidneys, ears, and eyes. AS is considered the second most common cause of hereditary renal failure, exhibiting varied clinical manifestations across different lifespans. The aim of this study is to investigate the clinical features and genetic profile of AS and to elucidate the genotype-phenotype correlation of AS.
View Article and Find Full Text PDFThe impact of medication regimen complexity on patient-related and clinical outcomes in kidney failure: a systematic review.
Expert Opin Pharmacother
January 2025
School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
Introduction: Kidney failure is a life-limiting condition that profoundly impacts an individual's quality of life. The significant medication burden on patients required to manage the comorbidities and complications of kidney failure can have implications for patient-reported and clinical outcomes.
Methods: This work systematically reviewed methods used to assess medication regimen complexity amongst adults with kidney failure, the associated patient-reported and clinical outcomes, and the effectiveness of interventions to address regimen complexity.
Chronic Kidney Disease Prevalence in India: A Systematic Review and Meta-Analysis From Community-Based Representative Evidence Between 2011 to 2023.
Nephrology (Carlton)
January 2025
Jawaharlal Institute of Post Graduate Medical Education and Research, Puducherry, India.
Chronic kidney disease (CKD) prevalence varies widely across different regions of India. We aimed to identify the status of CKD in India, by systematically reviewing the published community-based studies between the period of January 2011 to December 2023. PubMed, Scopus, and EMBASE were searched for peer-reviewed evidence.
View Article and Find Full Text PDFArtificial Intelligence to Predict Chronic Kidney Disease Progression to Kidney Failure: A Narrative Review.
Nephrology (Carlton)
January 2025
Faculty of Medicine, Dentistry & Health Sciences Melbourne, The University of Melbourne, Melbourne, Victoria, Australia.
Chronic kidney disease is characterised by the progressive loss of kidney function. However, predicting who will progress to kidney failure is difficult. Artificial Intelligence, including Machine Learning, shows promise in this area.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!