Acute kidney injury and COVID-19: the predictive power of BUN/albumin ratio for renal replacement therapy requirement.

Ir J Med Sci

Emergency Medicine Clinic, Adana City Training and Research Hospital, Health Sciences University, Mithat Ozhan Avenue, 01370, Yuregir, Adana, Turkey.

Published: December 2024

Objective: To investigate the predictive power of the BUN/albumin ratio (BAR) measured in the emergency department (ED) for the requirement of renal replacement therapy (RRT) in patients admitted to the intensive care unit (ICU) with severe COVID-19 pneumonia and acute kidney injury (AKI).

Materials And Methods: The study included 117 patients with AKI who were admitted to the ICU and had COVID-19 pneumonia detected on chest computed tomography (CT) taken in the ED's pandemic area between November 1, 2020, and June 1, 2021. The predictive power of laboratory values measured at the time of ED admission for the requirement of RRT was analyzed.

Results: Of the patients, 59.8% (n = 70) were male, with an average age of 71.7 ± 14.8 years. The mortality rate of the study was 35% (n = 41). During follow-up, 23.9% (n = 28) of the patients required RRT. Laboratory parameters measured at the time of ED admission showed that patients who required RRT had significantly higher BAR, BUN, and creatinine levels, and significantly lower albumin levels (all p < 0.001). ROC analysis to determine the predictive characteristics for RRT requirement revealed that the BAR had the highest AUC value (AUC, 0.885; 95% CI 0.825-0.945; p < 0.001). According to the study data, for BAR, a cut-off value of 1.7 resulted in a sensitivity of 96.4% and a specificity of 71.9%.

Conclusion: In patients with severe pneumonia who develop acute kidney injury, the BUN/albumin ratio may guide clinicians early in predicting the need for renal replacement therapy.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11845-024-03772-9DOI Listing

Publication Analysis

Top Keywords

predictive power
12
acute kidney
8
kidney injury
8
power bun/albumin
8
bun/albumin ratio
8
renal replacement
8
replacement therapy
8
covid-19 pneumonia
8
measured time
8
time admission
8

Similar Publications

We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically validated lexicons for detecting the eight emotions in Plutchik's theory. We show that EmoAtlas can match or surpass transformer-based natural language processing techniques, BERT or large language models like ChatGPT 3.

View Article and Find Full Text PDF

Photothermal therapy, in which a laser is an effective tool, is a promising method for cancer treatment. Laser parameters, including power, irradiation time, type of laser radiation (continuous or chopped), and the concentration of the photothermal agent, can affect the efficiency of this method. Therefore, this study investigated and compared the effects of different laser parameters on the efficiency of photothermal treatment for cervical cancer, which is the fourth most prevalent cancer in women.

View Article and Find Full Text PDF

Sleep tests commonly diagnose sleep disorders, but the diverse sleep-related biomarkers recorded by such tests can also provide broader health insights. In this study, we leveraged the uniquely comprehensive data from the Human Phenotype Project cohort, which includes 448 sleep characteristics collected from 16,812 nights of home sleep apnea test monitoring in 6,366 adults (3,043 male and 3,323 female participants), to study associations between sleep traits and body characteristics across 16 body systems. In this analysis, which identified thousands of significant associations, visceral adipose tissue (VAT) was the body characteristic that was most strongly correlated with the peripheral apnea-hypopnea index, as adjusted by sex, age and body mass index (BMI).

View Article and Find Full Text PDF

The failure of locked-segment landslides is associated with the destruction of locked segments that exhibit an energy accumulation effect. Thus, understanding their failure mode and instability mechanism for landslide hazard prevention and control is critical. In this paper, multiple instruments, such as tilt sensors, pore water pressure gauges, moisture sensors, matrix suction sensors, resistance strain gauges, miniature earth pressure sensors, a three-dimensional (3D) laser scanner, and a camera, were used to conduct the physical model tests on the rainfall-induced arch locked-segment landslide to analyze the resulting tilting deformation and evolution mechanism.

View Article and Find Full Text PDF

Reliable prediction of photovoltaic power generation is key to the efficient management of energy systems in response to the inherent uncertainty of renewable energy sources. Despite advances in weather forecasting, photovoltaic power prediction accuracy remains a challenge. This study presents a novel approach that combines genetic algorithms and dynamic neural network structure refinement to optimize photovoltaic prediction.

View Article and Find Full Text PDF

Want 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!