Acute Kidney Injury In Intensive Care Unit Research Articles

Incidence and outcome of Acute Kidney Injury in patients admitted in a level III ICU in Nepal: A retrospective, observational study

Background and aims: Acute kidney injury (AKI) is associated with increased mortality, morbidity, and hospital stay. AKI is seen in 20-60% of patients admitted to the intensive care unit (ICU), and mortality is as high as 50% if not managed timely. Burden of AKI is more in developing countries as compared to the developed ones. There is a paucity of published literature regarding incidence and outcome of AKI in critically ill patients from lower-middle income countries like Nepal. This study aimed to determine the incidence and outcome of AKI in patients admitted to a level III ICU in Nepal. Methods: This observational study was conducted in the ICU of Hospital for Advanced Medicine and Surgery (HAMS) Hospital, Kathmandu, Nepal. Data over a period of one year was curated from ICU registry. Eligible patients were screened and the incidence of AKI in ICU admitted patients along with their outcomes (length of ICU stay, need of RRT and ICU mortality) were observed. Results: Among 881 patients admitted to the ICU, 660 patients were enrolled for analysis. Of them, 14.2% of patients developed AKI during ICU stay, out of which 5.3% received RRT and 19.1% died. The median (IQR) length of ICU stay for those who developed AKI was 4 (3-7) days. The 34.0% patients who developed AKI had sepsis. Conclusion: Patients admitted to ICU in this study have high incidence of AKI. In patients who developed AKI, sepsis was the leading cause of ICU admission.

Epidemiology of Renal Replacement Therapy for Critically Ill Patients across Seven Health Jurisdictions.

Acute kidney injury (AKI) requiring treatment with renal replacement therapy (RRT) is a common complication after admission to an intensive care unit (ICU) and is associated with significant morbidity and mortality. However, the prevalence of RRT use and the associated outcomes in critically patients across the globe are not well described. Therefore, we describe the epidemiology and outcomes of patients receiving RRT for AKI in ICUs across several large health system jurisdictions. Retrospective cohort analysis using nationally representative and comparable databases from seven health jurisdictions in Australia, Brazil, Canada, Denmark, New Zealand, Scotland, and the USA between 2006 and 2023, depending on data availability of each dataset. Patients with a history of end-stage kidney disease receiving chronic RRT and patients with a history of renal transplant were excluded. A total of 4,104,480 patients in the ICU cohort and 3,520,516 patients in the mechanical ventilation cohort were included. Overall, 156,403 (3.8%) patients in the ICU cohort and 240,824 (6.8%) patients in the mechanical ventilation cohort were treated with RRT for AKI. In the ICU cohort, the proportion of patients treated with RRT was lowest in Australia and Brazil (3.3%) and highest in Scotland (9.2%). The in-hospital mortality for critically ill patients treated with RRT was almost fourfold higher (57.1%) than those not receiving RRT (16.8%). The mortality of patients treated with RRT varied across the health jurisdictions from 37 to 65%. The outcomes of patients who receive RRT in ICUs throughout the world vary widely. Our research suggests that differences in access to and provision of this therapy are contributing factors.

#1398 Linezolid adsorption during in vitro model of hemoadsorption with mini-module of HA380 cartridge

Abstract Background and Aims Septic shock is one of the most frequent causes in Intensive Care Unit (ICU) admission and is related to a very high risk of mortality. About one third of patients with sepsis develops acute kidney injury (AKI) which contributes to a worsening prognosis. AKI due to sepsis is the result of a dysregulated host immune response to infection, with the production of inflammatory mediators and cytokines that cause hemodynamic alterations, endothelial damage, apoptosis and, finally, immunoparalysis. The Jafron HA380 cartridge has been specifically designed for use in clinical conditions characterized by cytokine storm such as sepsis. Given the growing application of these hemoadsorption device in cases of septic AKI in ICU, an unsolved problem is whether these polymers adsorb drugs, including antibiotics. In vitro experiments were conducted to determine its adsorption capacity towards Linezolid (LZD) antibiotic. Method In vitro circulation was performed using a dedicated testing platform Galileo. A customized cartridge was built assembling mini-module components scaled in dimension towards HA380 and filled with 75 g of HA380 beads (25% of the regular size cartridge). Peristaltic pump was set at 250 mL/min. Four circulations were performed varying the initial mass of Linezolid in the tested solution (200, 400, 600, 1200 mg). Samples were collected after the first passage (FP) through the cartridge and every 5 or 10 minutes and Linezolid concentrations were measured. Adsorption was assessed considering the Removal Ratio (RR) and its kinetics. Results In vitro circulation confirms the affinity of beads material in binding Linezolid molecules. The kinetics shows an instantaneous and rapid adsorption in the very first part of the experiments. After that the adsorption rate decreases due to the decrease of antibiotic available in the solution. Among all the experiments, after the first passage of the solution through the cartridge, a RR higher than 70% has been achieved. After 100 passages of the solution into the cartridge, the adsorption reached about the 100% of RR. None of the amounts of Linezolid tested led to the cartridge saturation. A linear behavior between the mass injected in the solution and the mass adsorbed can be ascribable to the linear phase of Langmuir isotherm (see Fig.). Conclusion HA380 adsorbs significant amounts of Linezolid. The linear trend of the isotherm reveals a direct proportionality between binding sites of the sorbent material and the Linezolid tested. Further investigation using a higher quantity of Linezolid is necessary to reach the saturation of the cartridge and to understand the sorbent material capacity. These preliminary results highlight that there is an interaction that could affect the clinical outcome.

A Machine Learning Algorithm Predicting Acute Kidney Injury in Intensive Care Unit Patients (NAVOY Acute Kidney Injury): Proof-of-Concept Study.

Acute kidney injury (AKI) represents a significant global health challenge, leading to increased patient distress and financial health care burdens. The development of AKI in intensive care unit (ICU) settings is linked to prolonged ICU stays, a heightened risk of long-term renal dysfunction, and elevated short- and long-term mortality rates. The current diagnostic approach for AKI is based on late indicators, such as elevated serum creatinine and decreased urine output, which can only detect AKI after renal injury has transpired. There are no treatments to reverse or restore renal function once AKI has developed, other than supportive care. Early prediction of AKI enables proactive management and may improve patient outcomes. The primary aim was to develop a machine learning algorithm, NAVOY Acute Kidney Injury, capable of predicting the onset of AKI in ICU patients using data routinely collected in ICU electronic health records. The ultimate goal was to create a clinical decision support tool that empowers ICU clinicians to proactively manage AKI and, consequently, enhance patient outcomes. We developed the NAVOY Acute Kidney Injury algorithm using a hybrid ensemble model, which combines the strengths of both a Random Forest (Leo Breiman and Adele Cutler) and an XGBoost model (Tianqi Chen). To ensure the accuracy of predictions, the algorithm used 22 clinical variables for hourly predictions of AKI as defined by the Kidney Disease: Improving Global Outcomes guidelines. Data for algorithm development were sourced from the Massachusetts Institute of Technology Lab for Computational Physiology Medical Information Mart for Intensive Care IV clinical database, focusing on ICU patients aged 18 years or older. The developed algorithm, NAVOY Acute Kidney Injury, uses 4 hours of input and can, with high accuracy, predict patients with a high risk of developing AKI 12 hours before onset. The prediction performance compares well with previously published prediction algorithms designed to predict AKI onset in accordance with Kidney Disease: Improving Global Outcomes diagnosis criteria, with an impressive area under the receiver operating characteristics curve (AUROC) of 0.91 and an area under the precision-recall curve (AUPRC) of 0.75. The algorithm's predictive performance was externally validated on an independent hold-out test data set, confirming its ability to predict AKI with exceptional accuracy. NAVOY Acute Kidney Injury is an important development in the field of critical care medicine. It offers the ability to predict the onset of AKI with high accuracy using only 4 hours of data routinely collected in ICU electronic health records. This early detection capability has the potential to strengthen patient monitoring and management, ultimately leading to improved patient outcomes. Furthermore, NAVOY Acute Kidney Injury has been granted Conformite Europeenne (CE)-marking, marking a significant milestone as the first CE-marked AKI prediction algorithm for commercial use in European ICUs.

Adjuvant Lipoic acid Injection in Sepsis treatment in China (ALIS study): protocol for a randomised, single-blind, placebo-controlled trial

IntroductionSepsis is a life-threatening immune disorder resulting from an dysregulated host response to infection. Adjuvant therapy is a valuable complement to sepsis treatment. Lipoic acid has shown potential in attenuating...

Evaluation of Contrast-Enhanced Ultrasound in Diagnosis of Acute Kidney Injury of Patients in Intensive Care Unit.

Ultrasound can assess renal perfusion, but its role in the evaluation of acute kidney injury (AKI) is still unclear. This prospective cohort study was to investigate the value of contrast-enhanced ultrasound (CEUS) in the evaluation of AKI in intensive care unit (ICU) patients. Fifty-eight patients were recruited from ICU between October 2019 and October 2020, and CEUS was used to monitor the renal microcirculation perfusion within 24h after admission. Parameters included rise time (RT), time to peak intensity (TTP), amplitude of peak intensity (PI), area under the curve (AUC), time from peak to one half (TP1/2) of renal cortex and medulla. Ultrasonographical findings, demographics, laboratory, etc were collected for further analysis. There were 30 patients in the AKI group and 28 patients in the non-AKI group. The TTP, PI, TP1/2 of the cortex and the RT, TTP, TP1/2 of the medulla in the AKI group were significantly longer than in the non-AKI group (P < 0.05);. The TTP (OR = 1.261, 95% CI: 1.083-1.468, P = 0.003) (AUCs 0.733, Sen% 83.3, Spe%57.1), TP1/2 (OR = 1.079, 95% CI: 1.009-1.155, P = 0.027) (AUCs 0.658, Sen% 76.7, Spe%50.0) of the cortex and RT (OR = 1.453, 95% CI: 1.051-2.011, P = 0.024) (AUCs 0.686, Sen% 43.3, Spe%92.9) of the medulla were related to the AKI. Eight new-onset AKI cases occurred in the non-AKI group within 7 days, the RT, TTP, TP1/2 of the cortex and medulla were significantly longer in the new-onset AKI group than in the non-AKI group (P < 0.05), but serum creatinine and blood urea nitrogen were no differences between groups (P > 0.05). This study indicates CEUS can assess the renal perfusion in AKI. TTP and TP1/2 of the cortex and RT of the medulla can aid the diagnosis of AKI in ICU patients.

Perspectives of Pediatric Nephrologists, Intensivists and Nurses Regarding AKI Management and Expected Outcomes.

Acute kidney injury (AKI) in critically ill children is associated with increased risk for short- and long-term adverse outcomes. Currently, there is no systematic follow-up for children who develop AKI in intensive care unit (ICU). This study aimed to assess variation regarding management, perceived importance, and follow-up of AKI in the ICU setting within and between healthcare professional (HCP) groups. Anonymous, cross-sectional, web-based surveys were administered nationally to Canadian pediatric nephrologists, pediatric intensive care unit (PICU) physicians, and PICU nurses, via professional listservs. All Canadian pediatric nephrologists, PICU physicians, and nurses treating children in the ICU were eligible for the survey. N/A. Surveys included multiple choice and Likert scale questions on current practice related to AKI management and long-term follow-up, including institutional and personal practice approaches, and perceived importance of AKI severity with different outcomes. Descriptive statistics were performed. Categorical responses were compared using Chi-square or Fisher's exact tests; Likert scale results were compared using Mann-Whitney and Kruskal-Wallis tests. Surveys were completed by 34/64 (53%) pediatric nephrologists, 46/113 (41%) PICU physicians, and 82 PICU nurses (response rate unknown). Over 65% of providers reported hemodialysis to be prescribed by nephrology; a mix of nephrology, ICU, or a shared nephrology-ICU model was reported responsible for peritoneal dialysis and continuous renal replacement therapy (CRRT). Severe hyperkalemia was the most important renal replacement therapy (RRT) indication for both nephrologists and PICU physicians (Likert scale from 0 [not important] to 10 [most important]; median = 10, 10, respectively). Nephrologists reported a lower threshold of AKI for increased mortality risk; 38% believed stage 2 AKI was the minimum compared to 17% of PICU physicians and 14% of nurses. Nephrologists were more likely than PICU physicians and nurses to recommend long-term follow-up for patients who develop any AKI during ICU stay (Likert scale from 0 [none] to 10 [all patients]; mean=6.0, 3.8, 3.7, respectively) (P < .05). Responses from all eligible HCPs in the country could not obtained. There may be differences in opinions between HCPs that completed the survey compared to those that did not. Additionally, the cross-sectional design of our study may not adequately reflect changes in guidelines and knowledge since survey completion, although no specific guidelines have been released in Canada since survey dissemination. Canadian HCP groups have variable perspectives on pediatric AKI management and follow-up. Understanding practice patterns and perspectives will help optimize pediatric AKI follow-up guideline implementation.

Evaluation of Predictors, Kinetics of Renal Recovery and Outcomes of COVID-19 Patients with Acute Kidney Injury Admitted to Intensive Care Unit: An Observational Study.

The incidence of acute kidney injury (AKI) is greater than 50% among coronavirus disease-2019 (COVID-19) patients admitted to the intensive care unit (ICU). However, the literature on predictors and kinetics of renal recovery remains unclear. This observational study was conducted in a 30-bedded mixed ICU of a tertiary care center from May 2020 to July 2021. A total of 200 consecutive adult COVID-19 patients who had AKI in ICU were included. Using logistic regression with the best subset selection, predictors of renal recovery were identified. Outcomes and kinetics of AKI recovery were determined. Among 200 patients, 67 recovered from AKI, of which 38, 17, and 12 patients had transient AKI, persistent AKI, and acute kidney disease (AKD), respectively. A total of 25 patients had AKI relapse, primarily associated with hospital-acquired infections. Results of logistic regression showed that the combination of Acute Physiology and Chronic Health Evaluation (APACHE II) {odds ratio (OR) 1.1 [p < 0.001; 95% confidence interval (CI) 1.06-1.16]}, day onset of AKI [OR 1.6 (p = 0.001; 1.24-2.24)] and severity of AKI [OR 2.9 (p < 0.001; 2.03-4.36)] were the predictors associated with poor renal recovery. This model had sufficient discrimination with the area under the curve (AUC) of 0.86. Renal replacement therapy requirement and mortality among COVID-AKI patients were 68 and 84%, respectively. A higher APACHE II at admission, a longer time to onset of AKI, and the severity of AKI during ICU stay predicted poor renal recovery. Study results emphasize the need for stepping-up dialysis resources in the likely case of future waves of COVID-19. The relapse of AKI was associated with sepsis, and mortality rates were substantially high. Gudivada KK, Narayan SK, Narasimha A, Krishna B, Muralidhara KD. Evaluation of Predictors, Kinetics of Renal Recovery and Outcomes of COVID-19 Patients with Acute Kidney Injury Admitted to Intensive Care Unit: An Observational Study. Indian J Crit Care Med 2022;26(12):1293-1299.

POS-136 MANAGEMENT AND OUTCOMES OF SEPSIS ASSOCIATED ACUTE KIDNEY INJURY IN CRITICALLY ILL PATIENTS

Sepsis-associated acute kidney injury (AKI)remains a major cause of mortality in patients with critical illness and has an especially high health-related burden in developping countries. However, only a few clinical studies have focused on the clinical characteristics and prognosis of septic AKI, especially in low-income settings. Therefore, the aim of our study was to describe the clinical profile, management and outcome of critically ill patients with sepsis associated AKI. A retrospective observational study of critically ill patients with septic AKI was performed from March 2020 to June 2021 at our university hospital. Sepsis was diagnosed clinically by the presence of acute infection and new organ dysfunction.The presence of AKI was evaluated using the Acute Kidney Injury Network (AKIN) criteria. Patients with preexisting ESRD and those who did not fulfill at least one predefined criterion for AKI were excluded. A total of 105 patients with a median age of 58.9 years (31-78) were enrolled, including 69 and 36 patients with persistent and transient AKI, respectively. The mean SAPS II score was 51.8 (38-77). The primary source of sepsis was mainly abdominal (42.8%). AKI was defined by oliguria in 18 patients (17.1%), by creatinine elevation in 65 patients (61.9%), and by both criteria in 22 patients (21%). Septic AKI was associated with great aberrations in hemodynamics, with 71 patients (67.6%) requiring vasoactive therapy and 65 patients (61.9%) requiring mechanical ventilation. AKI severity according to the AKIN classification scheme was determined to be stage 1 in 32 patients (30.5%), stage 2 in 22 patients (20.9%), and stage 3 in 51 patients (48.6%). Overall, 75.2% of the cohort required renal replacement therapy (RRT). Hospital survival was 63.8% (n = 23) in patients with transient AKI and 43.5% (n =30) in patients with persistent AKI. Sepsis is the main cause of AKI in intensive care units, accounting for up to 50% of cases. Our results suggest that septic AKI is associated with higher disease severity scores at admission, requirement of vasoactive drugs, need for mechanical ventilation and increased hospital mortality. Further studies are required, especially in developping countries, to implement more preventive measures and therapeutic interventions to decrease CKD progression and mortality in these patients.

Risk factors for acute kidney injury after liver transplantation in intensive care unit: a retrospective cohort study.

ABSTRACTBACKGROUND:Acute kidney injury (AKI) is a frequent complication during the postoperative period following liver transplantation. Occurrence of AKI in intensive care unit (ICU) patients is associated with increased mortality and higher costs.OBJECTIVE:To evaluate occurrences of moderate or severe AKI among patients admitted to the ICU after liver transplantation and investigate characteristics associated with this complication.DESIGN AND SETTING:Single-center retrospective cohort study in a public hospital, Belo Horizonte, Brazil.METHODS:Forty-nine patients admitted to the ICU between January 2015 and April 2017 were included. AKI was defined from a modified Kidney Disease Improving Global Outcomes (KDIGO) score (i.e. based exclusively on serum creatinine levels).RESULTS:Eighteen patients (36.7%) developed AKI KDIGO 2 or 3; mostly KDIGO 3 (16 out of the 18 patients). Lactate level within the first six hours after ICU admission (odds ratio, OR: 1.3; 95% confidence interval, CI: 1.021-1.717; P = 0.034) and blood transfusion requirement within the first week following transplantation (OR: 8.4; 95% CI: 1.687-41.824; P = 0.009) were independently associated with development of AKI. Patients with AKI KDIGO 2 or 3 underwent more renal replacement therapy (72.2% versus 3.2%; P < 0.01), had longer hospital stay (20 days versus 15 days; P = 0.001), higher in-hospital mortality (44.4% versus 6.5%; P < 0.01) and higher mortality rate after one year (44.4% versus 9.7%; P = 0.01).CONCLUSION:Need for blood transfusion during ICU stay and hyperlactatemia within the first six postoperative hours after liver transplantation are independently associated with moderate or severe AKI. Developing AKI is apparently associated with poor outcomes.

Monocyte-to-lymphocyte ratio: a potential novel predictor for acute kidney injury in the intensive care unit

Monocyte-to-lymphocyte ratio (MLR) and neutrophil-to-lymphocyte ratio (NLR) are considered as surrogate inflammatory indexes. Previous studies indicated that NLR was associated with the development of septic acute kidney injury (AKI). The objective of the present study was to explore the value of MLR and NLR in the occurrence of AKI in intensive care unit (ICU) patients. The clinical details of adult patients (n = 1500) who were admitted to the ICU from January 2016 to December 2019 were retrospectively examined. AKI was diagnosed according to the Kidney Disease: Improving Global Outcomes criteria. The development of AKI was the main outcome, and the secondary outcome was in-hospital mortality. Overall, 615 (41%) patients were diagnosed with AKI. Both MLR and NLR were positively correlated with AKI incidence (p < 0.001). Multivariate logistic regression analysis suggested that the risk value of MLR for the occurrence of AKI was nearly three-fold higher than NLR (OR = 3.904, 95% CI: 1.623‒9.391 vs. OR = 1.161, 95% CI: 1.135‒1.187, p < 0.001). The areas under the receiver operating characteristic curve (AUC) for MLR and NLR in the prediction of AKI incidence were 0.899 (95% CI: 0.881‒0.917) and 0.780 (95% CI: 0.755‒0.804) (all p < 0.001), with cutoff values of 0.693 and 12.4. However, the AUC of MLR and NLR in the prediction of in-hospital mortality was 0.583 (95% CI: 0.546‒0.620, p < 0.001) and 0.564 (95% CI: 0.528‒0.601, p = 0.001). MLR, an inexpensive and widely available parameter, is a reliable biomarker in predicting the occurrence of AKI in ICU patients.

Research progress of renal resistive index in the evaluation of acute kidney injury

Acute kidney injury (AKI) is common in critically ill patients and it is directly related to the patient's prognosis and survival. Despite remaining uncertainties regarding the prevalence of AKI in intensive care unit (ICU), the overall incidence of AKI is relatively high, and prompt recognition is necessary to ensure the risk assessment, early diagnosis, clinical outcome, and treatment of critically ill patients. Doppler-based renal resistive index (RRI) mainly reflects vascular bed resistance state, which can be indirect to the extent of the damage of renal parenchyma. It is a relatively objective and quantitative evaluation, and is widely used in clinical prognosis of acute or chronic renal damage evaluation and judgment. This paper reviews the definition of RRI, the measurement methods of RRI, the application and progress of RRI in the field of AKI, the advantages and disadvantages of ultrasonic measurement of RRI, the long-term application of RRI, the effectiveness of RRI in predicting AKI, and the progress in clinical application.

Prediction of acute kidney injury in ICU with gradient boosting decision tree algorithms

PurposeTo predict acute kidney injury (AKI) in a large intensive care unit (ICU) database. Materials and methodsA total of 30,020 ICU admissions with 17,222 AKI episodes were extracted from the Medical Information Mart from Intensive Care (MIMIC)-III database. These were randomly divided into a training set and an independent testing set in a ratio of 4:1. Data pertaining to demographics, admission information, vital signs, laboratory tests, critical illness scores, medications, comorbidities, and intervention measures were collected. Logistic regression, random forest, LightGBM, XGBoost, and an ensemble model was used for early prediction of AKI occurrence and important feature extraction. The SHAP analysis was adopted to reveal the impact of prediction for each feature. ResultsThe ensemble model had the best overall performance for predicting AKI before 24 h, 48 h and 72 h. The F1 values were 0.915, 0.893, and 0.878, respectively. AUCs were 0.923, 0.903, and 0.895, respectively. ConclusionsBased on readily available electronic medical record (EMR) data, gradient boosting decision tree models are highly accurate at early AKI prediction in critically ill patients.

Entropy-Based Time Window Features Extraction for Machine Learning to Predict Acute Kidney Injury in ICU

Acute kidney injury (AKI) refers to rapid decline of kidney function and is manifested by decreasing urine output or abnormal blood test (elevated serum creatinine). Electronic health records (EHRs) is fundamental for clinicians and machine learning algorithms to predict the clinical outcome of patients in the Intensive Care Unit (ICU). Early prediction of AKI could automatically warn the clinicians to review the possible risk factors and act in advance to prevent it. However, the enormous amount of patient data usually consists of a relatively incomplete data set and is very challenging for supervised machine learning process. In this paper, we propose an entropy-based feature engineering framework for vital signs based on their frequency of records. In particular, we address the missing at random (MAR) and missing not at random (MNAR) types of missing data according to different clinical scenarios. Regarding its applicability, we applied it to establish a prediction model for future AKI in ICU patients using 4278 ICU admissions from a tertiary hospital. Our result shows that the proposed entropy-based features are feasible to be used in the AKI prediction model and its performance improves as the data availability increases. In addition, we study the performance of AKI prediction model by comparing different time gaps and feature windows with the proposed vital sign entropy features. This work could be used as a guidance for feature windows selection and missing data processing during the development of a prediction model in ICU.

Acute Kidney Injury Due to COVID-19 in Intensive Care Unit: An Analysis From a Latin-American Center.

Introduction: The kidney may be affected by coronavirus (COVID-19) in the setting of acute kidney injury (AKI). Data about AKI in intensive care unit (ICU) patients in Latin America are scarce. We aimed to evaluate the risk of AKI, dialysis (HD), and death in ICU COVID-19 patients in a Brazilian center.Methods: Analysis from medical records of COVID-19 patients in a Brazilian center.Results: A total of 95 patients were analyzed. There was male predominance (64.2%), median age: 64.9 years, and previous history of hypertension and diabetes in 51.6 and 27.4%, respectively. AKI was diagnosed in 54 (56.8%) patients, and 32 (59.2%) of them required HD. Mortality rate was 17.9%. AKI patients when compared with no-AKI were more frequently hypertensive/diabetic and more often needed organ support therapies. Workups depicted more anemia, lymphopenia, and higher levels of inflammatory markers and higher mortality. Comparing patients who had undergone death to survivors, they were older, more frequently diabetic, and had worse SAPS3 and SOFA scores and need for organ support therapies, AKI, and HD. Multinomial logistic regression revealed that hypertension (p = 0.018) and mechanical ventilation (p = 0.002) were associated with AKI; hypertension (p = 0.002), mechanical ventilation (p = 0.008), and use of vasopressor (p = 0.027) to HD patients; and age >65 years (p = 0.03) and AKI (p = 0.04) were risk factors for death.Conclusions: AKI was a common complication of ICU COVID-19 patients, and it was more frequent in patients with hypertension and need of organ support therapies. As well as age >65 years, AKI was an independent risk factor for death.

Role of Damage-Associated Molecular Patterns in Septic Acute Kidney Injury, From Injury to Recovery.

Damage-associated molecular patterns (DAMPs) are a group of immunostimulatory molecules, which take part in inflammatory response after tissue injury. Kidney-specific DAMPs include Tamm-Horsfall glycoprotein, crystals, and uromodulin, released by tubular damage for example. Non-kidney-specific DAMPs include intracellular particles such as nucleus [histones, high-mobility group box 1 protein (HMGB1)] and cytosol parts. DAMPs trigger innate immunity by activating the NRLP3 inflammasome, G-protein coupled class receptors or the Toll-like receptor. Tubular necrosis leads to acute kidney injury (AKI) in either septic, ischemic or toxic conditions. Tubular necrosis releases DAMPs such as histones and HMGB1 and increases vascular permeability, which perpetuates shock and hypoperfusion via Toll Like Receptors. In acute tubular necrosis, intracellular abundance of NADPH may explain a chain reaction where necrosis spreads from cell to cell. The nature AKI in intensive care units does not have preclinical models that meet a variation of blood perfusion or a variation of glomerular filtration within hours before catecholamine infusion. However, the dampening of several DAMPs in AKI could provide organ protection. Research should be focused on the numerous pathophysiological pathways to identify the relative contribution to renal dysfunction. The therapeutic perspectives could be strategies to suppress side effect of DAMPs and to promote renal function regeneration.

Prediction Models for AKI in ICU: A Comparative Study.

PurposeTo assess the performance of models for early prediction of acute kidney injury (AKI) in the Intensive Care Unit (ICU) setting.Patients and MethodsData were collected from the Medical Information Mart for Intensive Care (MIMIC)-III database for all patients aged ≥18 years who had their serum creatinine (SCr) level measured for 72 h following ICU admission. Those with existing conditions of kidney disease upon ICU admission were excluded from our analyses. Seventeen predictor variables comprising patient demographics and physiological indicators were selected on the basis of the Kidney Disease Improving Global Outcomes (KDIGO) and medical literature. Six models from three types of methods were tested: Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Decision Machine (LightGBM), and Convolutional Neural Network (CNN). The area under receiver operating characteristic curve (AUC), accuracy, precision, recall and F-measure (F1) were calculated for each model to evaluate performance.ResultsWe extracted the ICU records of 17,205 patients from MIMIC-III dataset. LightGBM had the best performance, with all evaluation indicators achieving the highest value (average AUC = 0.905, F1 = 0.897, recall = 0.836). XGBoost had the second best performance and LR, RF, SVM performed similarly (P = 0.082, 0.158 and 0.710, respectively) on AUC. The CNN model achieved the lowest score for accuracy, precision, F1 and AUC. SVM and LR had relatively low recall compared with that of the other models. The SCr level had the most significant effect on the early prediction of AKI onset in LR, RF, SVM and LightGBM.ConclusionLightGBM demonstrated the best capability for predicting AKI in the first 72 h of ICU admission. LightGBM and XGBoost showed great potential for clinical application owing to their high recall value. This study can provide references for artificial intelligence-powered clinical decision support systems for AKI early prediction in the ICU setting.

Impact of timing of initiation of dialysis on mortality of patients with acute kidney injury

Introduction: In Brazil, primary studies on this issue are still limited and the ideal timing of initiation of dialysis in severe acute kidney injury (AKI) still generates disagreements among experts. Objectives: To assess if the timing of initiation of dialysis is associated with the mortality of patients with AKI in intensive care unit (ICU). Patients and Methods: We retrospectively analyzed medical records of patients that developed severe AKI in the ICU. Bivariate analysis was carried out to compare data between groups of patients who underwent early dialysis (ED - initiated up to two days after the AKI diagnosis) and late dialysis (LD – initiated more than two days after the AKI diagnosis), while multivariate logistic regression was applied to identify factors associated with mortality. Results: Of the 76 patients included in the study, 27 (35.5%) were allocated in the ED group and 49 (64.5%) in the LD group. LD group had a higher frequency of sepsis [26 (53%) vs. 12 (44%); P = 0.472], while the ED group had a higher median number of dialysis sessions (6 vs. 3; P = 0.477) and higher total median time on dialysis (17.5 h vs. 13 h; P = 0.629). The overall mortality rate was 61.8% (n = 47) and of 76% (n = 22) in the ED group. The patients’ serum creatinine level at admission in the ICU was the only statistically significant risk factor for death [OR= 0.453 (95% CI= 0.257–0.801); P = 0.006]. Conclusion: The overall and in the ED group mortality rate was elevated, however, the timing of initiation of dialysis did not show statistically significant association with death. The serum creatinine at ICU admission seems to be an important mortality predictor.

Association of Contrast and Acute Kidney Injury in the Critically Ill: A Propensity-Matched Study

While acute kidney injury (AKI) was previously thought to be a significant adverse effect of radiocontrast media, recent studies have shown that radiocontrast is not associated with an increased risk of AKI in hospitalized patients. However, this topic has not been studied extensively in critically ill patients. The purpose of this this study was to determine the association of contrast with AKI in intensive care unit (ICU) patients.

Inverse Correlation Between Incidence and Mortality of Acute Kidney Injury in Critically Ill Patients: A Systematic Review.

The reported incidence and mortality of acute kidney injury (AKI) in patients in intensive care units (ICUs) is remarkably different even with standardized AKI criteria. The aim of this study was to investigate the correlation between the incidence and mortality of patients with AKI in ICUs. We systematically reviewed clinical studies regarding adult ICU patients with AKI using Kidney Disease: Improving Global Outcomes-equivalent criteria from 2004 to May 1, 2018. We searched MEDLINE, EMBASE, and Cochrane Library to investigate the correlation between the incidence and mortality of patients with AKI in each cohort. Studies with small number of participants (less than 500) were excluded. The correlation between the incidence of AKI and mortality of patients was evaluated using a regression model. Our review yielded 76 cohorts, comprising 564,455 patients in ICU (median age, 60.5 years; men, 59.5%). The mortality of all patients did not correlate with the incidence of AKI in each cohort; however, the mortality of patients with AKI significantly decreased [squared correlation coefficient (R) = 0.18, regression coefficient (β) = -0.25, P < 0.001] as the incidence of AKI increased. This correlation was also observed in a subgroup analysis limited to the clinical setting of general ICUs, and among patients with mild or severe AKI. An inverse correlation between the incidence of AKI and the mortality of patients with AKI may indicate an advantage of frequent AKI occurrence, possibly because of increased awareness and larger exposure to AKIs; further study is needed, however, to confirm the causality. The protocol was registered in PROSPERO database (CRD 42019129322).