scholarly journals Acute Kidney Injury and Renal Replacement Therapy in Critically Ill COVID-19 Patients: Risk Factors and Outcomes: A Single-Center Experience in Brazil

2020 ◽  
pp. 1-11
Author(s):  
Marisa Petrucelli Doher ◽  
Fabrício Rodrigues Torres de Carvalho ◽  
Patrícia Faria Scherer ◽  
Thaís Nemoto Matsui ◽  
Adriano Luiz Ammirati ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Critically Ill ◽  
Invasive Mechanical Ventilation ◽  
Group Versus ◽  
Kidney Injury ◽  
Multivariable Logistic Regression Analysis ◽  
Additional Risk Factor

<b><i>Background:</i></b> Critically ill patients with COVID-19 may develop multiple organ dysfunction syndrome, including acute kidney injury (AKI). We report the incidence, risk factors, associations, and outcomes of AKI and renal replacement therapy (RRT) in critically ill COVID-19 patients. <b><i>Methods:</i></b> We performed a retrospective cohort study of adult patients with COVID-19 diagnosis admitted to the intensive care unit (ICU) between March 2020 and May 2020. Multivariable logistic regression analysis was applied to identify risk factors for the development of AKI and use of RRT. The primary outcome was 60-day mortality after ICU admission. <b><i>Results:</i></b> 101 (50.2%) patients developed AKI (72% on the first day of invasive mechanical ventilation [IMV]), and thirty-four (17%) required RRT. Risk factors for AKI included higher baseline Cr (OR 2.50 [1.33–4.69], <i>p</i> = 0.005), diuretic use (OR 4.14 [1.27–13.49], <i>p</i> = 0.019), and IMV (OR 7.60 [1.37–42.05], <i>p</i> = 0.020). A higher C-reactive protein level was an additional risk factor for RRT (OR 2.12 [1.16–4.33], <i>p</i> = 0.023). Overall 60-day mortality was 14.4% {23.8% (<i>n</i> = 24) in the AKI group versus 5% (<i>n</i> = 5) in the non-AKI group (HR 2.79 [1.04–7.49], <i>p</i> = 0.040); and 35.3% (<i>n</i> = 12) in the RRT group versus 10.2% (<i>n</i> = 17) in the non-RRT group, respectively (HR 2.21 [1.01–4.85], <i>p</i> = 0.047)}. <b><i>Conclusions:</i></b> AKI was common among critically ill COVID-19 patients and occurred early in association with IMV. One in 6 AKI patients received RRT and 1 in 3 patients treated with RRT died in hospital. These findings provide important prognostic information for clinicians caring for these patients.

scholarly journals Comparison of Approaches for Prediction of Renal Replacement Therapy-Free Survival in Patients with Acute Kidney Injury

2021 ◽  
pp. 1-7
Author(s):  
Pattharawin Pattharanitima ◽  
Akhil Vaid ◽  
Suraj K. Jaladanki ◽  
Ishan Paranjpe ◽  
Ross O’Hagan ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Kidney Injury ◽  
Support Vector ◽  
Adaptive Boosting ◽  
Free Survival ◽  
Extreme Gradient Boosting

Background/Aims: Acute kidney injury (AKI) in critically ill patients is common, and continuous renal replacement therapy (CRRT) is a preferred mode of renal replacement therapy (RRT) in hemodynamically unstable patients. Prediction of clinical outcomes in patients on CRRT is challenging. We utilized several approaches to predict RRT-free survival (RRTFS) in critically ill patients with AKI requiring CRRT. Methods: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify patients ≥18 years old with AKI on CRRT, after excluding patients who had ESRD on chronic dialysis, and kidney transplantation. We defined RRTFS as patients who were discharged alive and did not require RRT ≥7 days prior to hospital discharge. We utilized all available biomedical data up to CRRT initiation. We evaluated 7 approaches, including logistic regression (LR), random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), multilayer perceptron (MLP), and MLP with long short-term memory (MLP + LSTM). We evaluated model performance by using area under the receiver operating characteristic (AUROC) curves. Results: Out of 684 patients with AKI on CRRT, 205 (30%) patients had RRTFS. The median age of patients was 63 years and their median Simplified Acute Physiology Score (SAPS) II was 67 (interquartile range 52–84). The MLP + LSTM showed the highest AUROC (95% CI) of 0.70 (0.67–0.73), followed by MLP 0.59 (0.54–0.64), LR 0.57 (0.52–0.62), SVM 0.51 (0.46–0.56), AdaBoost 0.51 (0.46–0.55), RF 0.44 (0.39–0.48), and XGBoost 0.43 (CI 0.38–0.47). Conclusions: A MLP + LSTM model outperformed other approaches for predicting RRTFS. Performance could be further improved by incorporating other data types.

Timing of renal replacement therapy and clinical outcomes in critically ill patients with severe acute kidney injury

2009 ◽  
Vol 24 (1) ◽  
pp. 129-140 ◽  
Author(s):  
Sean M. Bagshaw ◽  
Shigehiko Uchino ◽  
Rinaldo Bellomo ◽  
Hiroshi Morimatsu ◽  
Stanislao Morgera ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Clinical Outcomes ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Kidney Injury

scholarly journals Effect of Early vs Delayed Initiation of Renal Replacement Therapy on Mortality in Critically Ill Patients With Acute Kidney Injury

JAMA ◽  
2016 ◽  
Vol 315 (20) ◽  
pp. 2190 ◽  
Author(s):  
Alexander Zarbock ◽  
John A. Kellum ◽  
Christoph Schmidt ◽  
Hugo Van Aken ◽  
Carola Wempe ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Kidney Injury ◽  
Delayed Initiation
Sign in / Sign up

Export Citation Format

Share Document