Abstract Acute Kidney Injury Research Articles

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.

Increased risk of acute kidney injury in coronavirus disease patients with renin\u2013angiotensin\u2013aldosterone-system blockade use: a systematic review and meta-analysis

Acute kidney injury (AKI) is a severe complication of coronavirus disease (COVID-19) that negatively affects its outcome. Concern had been raised about the potential effect of renin–angiotensin–aldosterone system (RAAS) blockades on renal outcomes in COVID-19 patients. However, the association between RAAS blockade use and incident AKI in COVID-19 patients has not been fully understood. We investigated the association between RAAS blockade exposure and COVID-19-related AKI in hospitalized patients through meta-analysis. Electronic databases were searched up to 24th December 2020. Summary estimates of pooled odds ratio (OR) of COVID-19-related AKI depending on RAAS blockade exposure were obtained through random-effects model. The random-effect meta-analysis on fourteen studies (17,876 patients) showed that RAAS blockade use was significantly associated with increased risk of incident AKI in hospitalized COVID-19 patients (OR 1.68; 95% confidence interval 1.19–2.36). Additional analysis showed that the association of RAAS blockade use on COVID-19-related AKI remains significant even after stratification by drug class and AKI severity. RAAS blockade use is significantly associated with the incident AKI in hospitalized COVID-19 patients. Therefore, careful monitoring of renal complications is recommended for COVID-19 patients with recent RAAS blockade use due to the potential risk of AKI.

Acute Kidney Injury and Renal Replacement Therapy

Acute kidney injury (AKI) is a common syndrome encountered in critical illness and is associated with significant morbidity and increased mortality. Despite attempts to prevent the development of AKI, its incidence continues to rise, probably due to increased recognition in the setting of clearer definitions of the stages of AKI. Despite advances in the field of Nephrology, the treatment of AKI and its complications remains difficult in clinical practice. Critical care clinicians must have an understanding of the current definitions, pathophysiology, and treatment modalities. Renal replacement therapy (RRT) is a mainstay of treatment, but a lack of consensus regarding the optimal timing for initiation remains. There is a need for further research regarding both the timing of initiation of RRT and biomarkers that might allow earlier detection, differentiation of etiologies and monitoring of interventions. This review contains 3 figures, 4 tables, and 31 references Key Words: acute kidney injury (AKI), KDIGO, renal replacement therapy (RRT), risk, injury, failure, loss of kidney function, end stage renal disease (RIFLE), nephrology

Analysis of the Impact of Medical Features and Risk Prediction of Acute Kidney Injury for Critical Patients Using Temporal Electronic Health Record Data With Attention-Based Neural Network.

Acute kidney injury (AKI) is one of the most severe consequences of kidney injury, and it will also cause or aggravate the complications by the fast decline of kidney excretory function. Accurate AKI prediction, including the AKI case, AKI stage, and AKI onset time interval, can provide adequate support for effective interventions. Besides, discovering how the medical features affect the AKI result may also provide supporting information for disease treatment. An attention-based temporal neural network approach was employed in this study for AKI prediction and for the analysis of the impact of medical features from temporal electronic health record (EHR) data of patients before AKI diagnosis. We used the publicly available dataset provided by the Medical Information Mart for Intensive Care (MIMIC) for model training, validation, and testing, and then the model was applied in clinical practice. The improvement of AKI case prediction is around 5% AUC (area under the receiver operating characteristic curve), and the AUC value of AKI stage prediction on AKI stage 3 is over 82%. We also analyzed the data by two steps: the associations between the medical features and the AKI case (positive or inverse) and the extent of the impact of medical features on AKI prediction result. It shows that features, such as lactate, glucose, creatinine, blood urea nitrogen (BUN), prothrombin time (PT), and partial thromboplastin time (PTT), are positively associated with the AKI case, while there are inverse associations between the AKI case and features such as platelet, hemoglobin, hematocrit, urine, and international normalized ratio (INR). The laboratory test features such as urine, glucose, creatinine, sodium, and blood urea nitrogen and the medication features such as nonsteroidal anti-inflammatory drugs, agents acting on the renin–angiotensin system, and lipid-lowering medication were detected to have higher weights than other features in the proposed model, which may imply that these features have a great impact on the AKI case.

A validation study comparing existing prediction models of acute kidney injury in patients with acute heart failure

Acute kidney injury (AKI) is a common complication in acute heart failure (AHF) and is associated with prolonged hospitalization and increased mortality. The aim of this study was to externally validate existing prediction models of AKI in patients with AHF. Data for 10,364 patients hospitalized for acute heart failure between 2008 and 2018 were extracted from the Chang Gung Research Database and analysed. The primary outcome of interest was AKI, defined according to the KDIGO definition. The area under the receiver operating characteristic (AUC) curve was used to assess the discrimination performance of each prediction model. Five existing prediction models were externally validated, and the Forman risk score and the prediction model reported by Wang et al. showed the most favourable discrimination and calibration performance. The Forman risk score had AUCs for discriminating AKI, AKI stage 3, and dialysis within 7 days of 0.696, 0.829, and 0.817, respectively. The Wang et al. model had AUCs for discriminating AKI, AKI stage 3, and dialysis within 7 days of 0.73, 0.858, and 0.845, respectively. The Forman risk score and the Wang et al. prediction model are simple and accurate tools for predicting AKI in patients with AHF.

ACUTE KIDNEY INJURY (AKI) PADA KEHAMILAN

Acute Kidney Injury (AKI) in pregnancy remains a cause for fetomaternal morbidity and mortality, particularly in developing countries. Hypertensive complications of pregnancy (preeclampsia/eclampsia, HELLP syndrome) remains the leading cause of AKI in pregnancy. A set of systemic and renal physiological adaptive mechanisms occur during a normal gestation that will cause several changes in laboratory parameters of renal function, electrolytes, fluid and acid – base balance. Diagnosis of AKI in pregnancy is based on the serum creatinine increase and reduction of urine output. Management of AKI in pregnancy requires a multidisciplinary approach between nephrologists and obstetricians for optimizing care for both mother and child. In approaching AKI in pregnant woman, emphasis should be placed on making early and accurate diagnosis to allow prompt intervention and to facilitate recovery from AKI.

Long non-coding RNA SNHG14 aggravates LPS-induced acute kidney injury through regulating miR-495-3p/HIPK1.

Acute kidney injury (AKI) is a complex syndrome with an abrupt decrease of kidney function, which is associated with high morbidity and mortality. Sepsis is the common cause of AKI. Mounting evidence has demonstrated that long non-coding RNAs (lncRNAs) play critical roles in the development and progression of sepsis-induced AKI. In this study, we aimed to illustrate the function and mechanism of lncRNA SNHG14 in lipopolysaccharide (LPS)-induced AKI. We found that SNHG14 was highly expressed in the plasma of sepsis patients with AKI. SNHG14 inhibited cell proliferation and autophagy and promoted cell apoptosis and inflammatory cytokine production in LPS-stimulated HK-2 cells. Functionally, SNHG14 acted as a competing endogenous RNA (ceRNA) to negatively regulate miR-495-3p expression in HK-2 cells. Furthermore, we identified that HIPK1 is a direct target of miR-495-3p in HK-2 cells. We also revealed that the SNHG14/miR-495-3p/HIPK1 interaction network regulated HK-2 cell proliferation, apoptosis, autophagy, and inflammatory cytokine production upon LPS stimulation. In addition, we demonstrated that the SNHG14/miR-495-3p/HIPK1 interaction network regulated the production of inflammatory cytokines (TNF-α, IL-6, and IL-1β) via modulating NF-κB/p65 signaling in LPS-challenged HK-2 cells. In conclusion, our findings suggested a novel therapeutic axis of SNHG14/miR-495-3p/HIPK1 to treat sepsis-induced AKI.

Acute Kidney Injury Post-Percutaneous Nephrolithotomy (PNL): Prospective Outcomes from a University Teaching Hospital.

Acute Kidney Injury (AKI) after percutaneous nephrolithotomy (PNL) is a significant complication, but evidence on its incidence is bereft in the literature. The objective of this prospective observational study was to analyze the incidence of post-PNL AKI and the potential risk factors and outcomes. Demographic data collected included age, gender, body mass index (BMI), comorbidities (hypertension, diabetes mellitus), and drug history—particularly angiotensin converting enzyme inhibitors (ACE inhibitors), angiotensin II receptor blockers and beta blockers. Laboratory data included serial serum creatinine measured pre- and postoperation (12, 24, and 48 h), hemoglobin (Hb), total leucocyte count (TLC), Prothrombin time (PT), serum uric acid and urine culture. Stone factors were assessed by noncontrast computerized tomography of kidneys, ureter and bladder (NCCT KUB) and included stone burden, location and Hounsfield values. Intraoperative factors assessed were puncture site, tract size, tract number, operative time, the need for blood transfusion and stone clearance. Postoperative complications were documented using the modified Clavien–Dindo grading system and patients with postoperative AKI were followed up with serial creatinine measurements up to 1 year. Among the 509 patients analyzed, 47 (9.23%) developed postoperative AKI. Older patients, with associated hypertension and diabetes mellitus, those receiving ACE inhibitors and with lower preoperative hemoglobin and higher serum uric acid, had higher incidence of AKI. Higher stone volume and density, staghorn stones, multiple punctures and longer operative time were significantly associated with postoperative AKI. Patients with AKI had an increased length of hospital stay and 17% patients progressed to chronic kidney disease (CKD). Cut-off values for patient age (39.5 years), serum uric acid (4.05 mg/dL) and stone volume (673.06 mm3) were assessed by receiver operating characteristic (ROC) curve analysis. Highlighting the strong predictors of post-PNL AKI allows early identification, proper counseling and postoperative planning and management in an attempt to avoid further insult to the kidney.

Different Biomarkers of Acute kidney Injury in Cancer Patients

Acute Kidney Injury (AKI) occurs if the kidneys suddenly lose their ability to remove waste products. When the kidneys lose their ability to filter, dangerous levels of waste products can accumulate, which can upset the chemical composition of the blood and urine. Chemotherapy is one of the methods used to treat or temporarily reduce cancer by using certain medications. The main task of this treatment is to kill cancer cells without seriously damaging the surrounding tissues. However, this type of treatment also has destructive effects on healthy cells and tissues in the body. Researchers studying cancer patients undergoing chemotherapy found that people undergoing this type of treatment may develop serious kidney problems and be forced to use treatments such as dialysis and kidney transplants. Research showed that people with more severe cancers and advanced tumors are more likely to have acute kidney injury than those with early-stage cancer. AKI biomarkers can be selected from the patient's serum, urine, or body imaging components. Various studies showed that urine is a source of the best markers in AKI. Biomarkers in plasma and urine, such as N-acetyl-β-glucosaminidase, Cystatin-C, β2-microglobulin , Cysteine-Rich Protein, Osteopontin, Fetuin-A, Kidney Injury Molecule-1, Liver-type fatty acid-binding protein, Netrin-1, Neutrophil gelatinase-associated lipocalin, and interleukin-18 are effective tools for early detection of AKI. In this review study, an attempt was made to collect biomarkers related to AKI disease.

Acute kidney injury adversely affects the clinical course of acute myeloid leukemia patients undergoing induction chemotherapy

Acute kidney injury (AKI) complicates the clinical course of hospitalized patients by increasing need for intensive care treatment and mortality. There is only little data about its impact on AML patients undergoing intensive induction chemotherapy. In this study, we analyzed the incidence as well as risk factors for AKI development and its impact on the clinical course of AML patients undergoing induction chemotherapy. We retrospectively analyzed data from 401 AML patients undergoing induction chemotherapy between 2007 and 2019. AKI was defined and stratified according to KIDGO criteria by referring to a defined baseline serum creatinine measured on day 1 of induction chemotherapy. Seventy-two of 401 (18%) AML patients suffered from AKI during induction chemotherapy. AML patients with AKI had more days with fever (7 vs. 5, p = 0.028) and were more often treated on intensive care unit (45.8% vs. 10.6%, p < 0.001). AML patients with AKI had a significantly lower complete remission rate after induction chemotherapy and, with 402 days, a significantly shorter median overall survival (OS) (median OS for AML patients without AKI not reached). In this study, we demonstrate that the KIDGO classification allows mortality risk stratification for AML patients undergoing induction chemotherapy. Relatively mild AKI episodes have impact on the clinical course of these patients and can lead to chronic impairment of kidney function. Therefore, we recommend incorporating risk factors for AKI in decision-making considering nutrition, fluid management, as well as the choice of potentially nephrotoxic medication in order to decrease the incidence of AKI.

Determinants of Outcomes of Acute Kidney Injury: Clinical Predictors and Beyond.

Acute kidney injury (AKI) is a common clinical syndrome characterized by rapid impairment of kidney function. The incidence of AKI and its severe form AKI requiring dialysis (AKI-D) has been increasing over the years. AKI etiology may be multifactorial and is substantially associated with increased morbidity and mortality. The outcome of AKI-D can vary from partial or complete recovery to transitioning to chronic kidney disease, end stage kidney disease, or even death. Predicting outcomes of patients with AKI is crucial as it may allow clinicians to guide policy regarding adequate management of this problem and offer the best long-term options to their patients in advance. In this manuscript, we will review the current evidence regarding the determinants of AKI outcomes, focusing on AKI-D.

Health Record–Based Alert to Improve Recognition of AKI in Hospitalized Patients

Acute kidney injury (AKI) in hospitalized patients is associated with poor outcomes but often is unrecognized. In this multicenter U.S. trial,

Acute Kidney Injury: Epidemiology, Pathophysiology, Repair Mechanisms

Acute kidney injury (AKI) is a major complication in critically ill patients and affects up to 50% of those admitted to intensive care units. Causes of AKI include patient specific factors (susceptibility: e.g. age, pre-existing chronic kidney disease, chronic heart failure, diabetes) and patient unspecific factors (exposure: e.g. sepsis, hypovolemia, cardiac surgery, nephrotoxin application). Mortality of severe AKI is in the range of 40 - 50%.AKI is accompanied by volume overload, electrolyte disorders, acidosis, and uremia. The diagnosis of AKI is based on an increase of creatinine levels and/or a decrease in urine output within 7 days after an insult. These 2 markers are late und unspecific, especially with regard to early identification of patients at risk of AKI. New AKI markers have been investigated within the last decade including NGAL (neutrophil gelatinase-associated lipocalin), the product of IGFBP-7 (insulin like growth factor binding protein 7) and TIMP-2 (tissue inhibitor of metalloproteinase 2), KIM-1 (kidney injury molecule 1) and the cysteine-protease-inhibitor cystatin C. New markers or a panel of new markers might improve the diagnosis of patients at risk of AKI in the future.There are currently no specific therapeutics in the treatment of AKI. Therefore, the prevention of AKI is of an utmost importance. The recommended preventive measures include optimization of hemodynamics and volume status, close monitoring of creatinine levels and urine output, avoidance or discontinuation of nephrotoxic drugs, normoglycemia and the application of alternatives to radiocontrast agents if possible.As the long term prognosis of AKI highly depends on renal recovery, the 2 major goals for the future will be 1) the early identification of patients at AKI risk and 2) the support of renal recovery of AKI patients.

Pathology of COVID-19-associated acute kidney injury.

Acute kidney injury (AKI) is common among hospitalized patients with coronavirus disease 2019 (COVID-19), with the occurrence of AKI ranging from 0.5% to 80%. An improved knowledge of the pathology of AKI in COVID-19 is crucial to mitigate and manage AKI and to improve the survival of patients who develop AKI during COVID-19. In this review, we summarize the published cases and case series of various kidney pathologies seen with COVID-19. Both live kidney biopsies and autopsy series suggest acute tubular injury as the most commonly encountered pathology. Collapsing glomerulopathy and thrombotic microangiopathy are other encountered pathologies noted in both live and autopsy tissues. Other rare findings such as anti-neutrophil cytoplasmic antibody vasculitis, anti-glomerular basement membrane disease and podocytopathies have been reported. Although direct viral infection of the kidney is possible, it is certainly not a common or even widespread finding reported at the time of this writing (November 2020).

Expressions and related mechanisms of miR-212 and KLF4 in rats with acute kidney injury.

Acute kidney injury (AKI) occurs in 30%-70% of critically ill patients. Multiple organ failure (MOF), which is most often secondary to hypotension and septicemia, is a global public health problem. The prognosis of patients is poor. Currently, there is no specific therapeutic method. Finding new therapeutic targets is significant to improve the prognosis of AKI patients. This study explores expressions and related mechanisms of miR-212 and Kruppel-like factor 4 (KLF4) in rats with AKI. Sixty Wistar rats were randomly divided into 6 groups: Control group, sham operation group, model group, miR-212-agomir group, miR-212-antagomir group, miR-212-agomir+APTO-253 (joint group), n = 10. The expressions of miR-212, KLF4, inflammatory factors [tumor necrosis factor α (TNF-α), interleukin 6 (IL-6)], oxidative stress factors [superoxide dismutase (SOD), malondialdehyde (MDA)], and apoptosis-related proteins (bax, bcl-2) in renal tissue of rats were detected, and the relationship between miR-212 and KLF4 and the severity of AKI in rats were analyzed. The expression level of miR-212 increased (P < 0.05) and the expression level of KLF4 decreased (P < 0.05) in renal tissue of rats with AKI. miR-212 was negatively correlated with KLF4 expression (P < 0.05). MiR-212 was positively correlated with expressions of TNF-α, IL-6, MDA, and bax (P < 0.05), negatively correlated with expressions of SOD and bcl-2 (P < 0.05), KLF4 was negatively correlated with expressions of TNF-α, IL-6, MDA and bax (P < 0.05), and positively correlated with expressions of SOD and bcl-2 (P < 0.05). MiR-212 mimics can inhibit the luciferase activity of Wt-KLF4 (P < 0.05), and miR-212 inhibitor can promote the luciferase activity of Wt-KLF4 (P < 0.05). Down-regulation of miR-212 plays a protective role by targeting up-regulation of KLF4 to inhibit renal tissue inflammation, oxidative stress, and apoptosis in rats with AKI, which may be a potential target for clinical treatment of AKI in the future.

Маркеры острого повреждения почек. перспективы их применения в практической деятельности

Acute kidney injury (AKI) is a common clinical syndrome. Its variety of presentation explains the absence of “kidney troponin”. Many research projects of new biomarkers are ongoing now. The enormous number of biomarkers has been identified already. It makes difficult to choose the correct test and dictates the importance of the fastest and most accurate introduction of AKI biomarkers into clinical practice. The integration of appropriately selected biomarkers in routine clinical practice for high-risk patients of AKI is very important. Currently, serum creatinine (sCr) and urine output are used to define AKI in accordance with the definition of KDIGO (Kidney Disease: Improving Global Outcomes), which have a number of significant limitations for practitioners, including the inability to diagnose AKI before serum creatinine levels increase. Practitioners need systematic information about the latest AKI markers and possible situations, when and for which patient groups they can be used. This is the main goal of our review. Keywords: acute kidney injury, biomarkers, NGAL, TIMP-2, IGFBP7, cystatin C, markers, injury, kidney stress For citation: Schelkanovtseva ES, Mironova OIu, Fomin VV. Biomarkers of acute kidney disease. Potential application in practice. Consilium Medicum. 2021; 23 (1): 15–19. DOI: 10.26442/20751753.2021.1.200729

Evaluating the Effect of Acetazolamide on the Prevention of Post-operative Acute Kidney Injury after Coronary Artery Bypass Grafting Surgery: A Randomized, Open-labeled Clinical Trial.

Acute kidney injury (AKI) is a common complication after coronary artery bypass grafting (CABG) surgery and can be linked to the increased morbidity and mortality. Therefore, in the present study, the effect of preoperative administration of acetazolamide was evaluated to investigate whether it could prevent occurrence of post-operative AKI after CABG surgery. In this randomized controlled clinical trial, 130 patients who were candidates to undergo elective CABG surgery from January 21, 2020 to February 8, 2021 were randomly allocated to intervention group (receiving 500 mg of acetazolamide orally 2 h preoperatively) and control group. The patients were evaluated for AKI based on the kidney disease- improving global outcomes (KDIGO) criteria based on their serum creatinine (SCr) level and urine output until 7 days postoperatively. There was no significant difference in baseline demographics between the two groups. The total incidence of AKI was measured as 43%. Analysis of post-operative AKI incidence showed no statistically significant difference between the two groups (P = 0.860). Mean post-operative SCr level on day 1 was significantly higher in the acetazolamide group (P = 0.036). A significant difference was found in length of hospitalization stay between the groups, which was higher in the control group (P = 0.006). Our results did not demonstrate a significant protective effect of acetazolamide on incidence of post-operative AKI in the patients undergone elective on-pump CABG surgery.

Bladder urine oxygen partial pressure monitoring: Could it be a tool for early detection of acute kidney injury?

ABSTRACT Acute kidney injury (AKI) necessitating renal-replacement therapy has been associated with high mortality rates in critically ill patients. Usual methods to study AKI encompass the assessment of serum and urine biomarkers. Hypoxia is a major pathophysiological feature of AKI, which necessitates continuous bedside monitoring of renal tissue oxygenation in intensive care unit (ICU) patients. Research has made continuous bladder urine oxygen pressure (PuO2) monitoring possible in humans. Although the value of bladder PuO2 does not represent an absolute value of medullary tissue oxygen pressure (Po2), bladder PuO2 can be considered a window into the renal medullary oxygenation. Bladder PuO2 can be monitored by using probes with oxygen sensors inserted into the urinary bladder. Additionally, PuO2 can be measured manually by using a blood gas analyzer machine. PuO2 monitoring can be potentially helpful in early diagnosis and/or prevention of AKI and guide therapeutic interventions aimed at improving renal oxygen delivery in those patients.

Optimization of the Classic Transfer-Stacking Model Migration Algorithm: A Way to Solve Time-Varying Performance Degradation of Acute Kidney Injury Clinical Prediction Model

Acute Kidney Injury (AKI) is one of the most common acute and critical illnesses in general wards and intensive care units. Its high morbidity and high fatality rate have become a major global public health problem. There are often serious lags in clinical diagnosis of AKI. Early diagnosis and timely intervention and effective care become critical. The use of electronic medical record data to build an AKI risk prediction model has been proven to help prevent the occurrence of AKI. However, in actual clinical applications, the distribution of historical data and new data will continue to vary over time, resulting in a significant decrease in the performance of the model. How to solve the problem of model performance degradation over time will be a core challenge for the long-term use of predictive models in clinical applications. Aiming at the above problems, this paper studies the classic Transfer-Stacking model migration algorithm. Aiming at the lack of this algorithm, such as the loss of a large amount of feature information of the target domain and poor fit when integrating the model of the target domain, the Accumulate-Transfer-Stacking algorithm is proposed to improve it. Improvements include: 1) Optimize the input vector and model integration algorithm of Transfer-Stacking’s target domain model. 2) Optimize Transfer-Stacking from a single-source domain model to a multi-source domain model. The experimental results show that for the improved algorithm proposed in this paper when the data is sufficient and insufficient, the average AUC value of the model on the data of subsequent years is 0.89 and 0.87, and the average F1 Score value is 0.45 and 0.36. Moreover, this method is significantly better than the unimproved Transfer-Stacking algorithm and baseline method, and can effectively overcome the problem of data distribution heterogeneity caused by time factors.

ACE2 activator diminazene aceturate exerts renoprotective effects in gentamicin-induced acute renal injury in rats

Acute Kidney Injury (AKI) comprises a rapidly developed renal failure and is associated with high mortality rates. The Renin-Angiotensin System (RAS) plays a pivotal role in AKI, as the over-active RAS axis exerts major deleterious effects in disease progression. In this sense, the conversion of Angiotensin II (Ang II) into Angiotensin-(1-7) (Ang-(1-7)) by the Angiotensin-converting enzyme 2 (ACE2) is of utmost importance to prevent worse clinical outcomes. Previous studies reported the beneficial effects of oral diminazene aceturate (DIZE) administration, an ACE2 activator, in renal diseases models. In the present study, we aimed to evaluate the therapeutic effects of DIZE administration in experimental AKI induced by gentamicin (GM) in rats. Our findings showed that treatment with DIZE improved renal function and tissue damage by increasing Ang-(1-7) and ACE2 activity, and reducing TNF-α. These results corroborate with a raising potential of ACE2 activation as a strategy for treating AKI.