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Introduction: The current definition of acute kidney injury (AKI) includes increased serum creatinine (sCr) concentration and decreased urinary output (UO). Recent studies suggest that the standard UO threshold of 0.5 ml/kg/h may be suboptimal. This study aimed to develop and validate a novel UO-based AKI classification system that improves mortality prediction and patient stratification., Methods: Data were obtained from the MIMIC-IV and eICU databases. The development process included (1) evaluating UO as a continuous variable over 3-, 6-, 12-, and 24-h periods; (2) identifying 3 optimal UO cutoff points for each time window (stages 1, 2, and 3); (3) comparing sensitivity and specificity to develop a unified staging system; (4) assessing average versus persistent reduced UO hourly; (5) comparing the new UO-AKI system to the KDIGO UO-AKI system; (6) integrating sCr criteria with both systems and comparing them; and (7) validating the new classification with an independent cohort. In all these steps, the outcome was hospital mortality. Another analyzed outcome was 90-day mortality. The analyses included ROC curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and logistic and Cox regression analyses., Results: From the MIMIC-IV database, 35,845 patients were included in the development cohort. After comparing the sensitivity and specificity of 12 different lowest UO thresholds across four time frames, 3 cutoff points were selected to compose the proposed UO-AKI classification: stage 1 (0.2-0.3 mL/kg/h), stage 2 (0.1-0.2 mL/kg/h), and stage 3 (< 0.1 mL/kg/h) over 6 h. The proposed classification had better discrimination when the average was used than when the persistent method was used. The adjusted odds ratio demonstrated a significant stepwise increase in hospital mortality with advancing UO-AKI stage. The proposed classification combined or not with the sCr criterion outperformed the KDIGO criteria in terms of predictive accuracy-AUC-ROC 0.75 (0.74-0.76) vs. 0.69 (0.68-0.70); NRI: 25.4% (95% CI: 23.3-27.6); and IDI: 4.0% (95% CI: 3.6-4.5). External validation with the eICU database confirmed the superior performance of the new classification system., Conclusion: The proposed UO-AKI classification enhances mortality prediction and patient stratification in critically ill patients, offering a more accurate and practical approach than the current KDIGO criteria., (© 2024. The Author(s).)

Acute kidney injury (AKI) is a common problem in critically ill patients and is associated with increased morbidity and mortality. Since 2012, AKI has been defined according to the KDIGO (Kidney Disease Improving Global Outcome) guidelines. As some biomarkers are now available that can provide useful clinical information, a new definition including a new stage 1S has been proposed by an expert group of the Acute Disease Quality Initiative (ADQI). At this stage, classic AKI criteria are not yet met, but biomarkers are already positive defining subclinical AKI. This stage 1S is associated with a worse patient outcome, regardless of the biomarker chosen. The PrevAKI and PrevAKI-Multicenter trial also showed that risk stratification with a biomarker and implementation of the KDIGO bundle (in the high-risk group) can reduce the rate of moderate and severe AKI. In the absence of a successful clinical trial, conservative management remains the primary focus of treatment. This mainly involves optimization of hemodynamics and an individualized (restrictive) fluid management. The STARRT-AKI trial has shown that there is no benefit from accelerated initiation of renal replacement therapy. However, delaying too long might be associated with potential harm, as shown in the AKIKI2 study. Prospective studies are needed to determine whether artificial intelligence will play a role in AKI in the future, helping to guide treatment decisions and improve outcomes., (© 2024. The Author(s).)

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses., (© 2024. The Author(s).)

Objectives: To compare performances of a classifier that leverages language models when trained on synthetic versus authentic clinical notes., Materials and Methods: A classifier using language models was developed to identify acute renal failure. Four types of training data were compared: (1) notes from MIMIC-III; and (2, 3, and 4) synthetic notes generated by ChatGPT of varied text lengths of 15 (GPT-15 sentences), 30 (GPT-30 sentences), and 45 (GPT-45 sentences) sentences, respectively. The area under the receiver operating characteristics curve (AUC) was calculated from a test set from MIMIC-III., Results: With RoBERTa, the AUCs were 0.84, 0.80, 0.84, and 0.76 for the MIMIC-III, GPT-15, GPT-30- and GPT-45 sentences training sets, respectively., Discussion: Training language models to detect acute renal failure from clinical notes resulted in similar performances when using synthetic versus authentic training data., Conclusion: The use of training data derived from protected health information may not be needed., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Current classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear., Methods: This retrospective study identified patients with Sepsis-3 who developed AKI within 48-h of intensive care unit admission using Medical Information Mart for Intensive Care-IV database. We used latent class mixed modelling to identify early creatinine trajectory-based classes of AKI in critically ill patients with sepsis. Our primary outcome was development of acute kidney disease (AKD). Secondary outcomes were composite of AKD or all-cause in-hospital mortality by day 7, and AKD or all-cause in-hospital mortality by hospital discharge. We used multivariable regression to assess impact of creatinine trajectory-based classification on outcomes, and eICU database for external validation., Results: Among 4197 patients with AKI in critically ill patients with sepsis, we identified eight creatinine trajectory-based classes with distinct characteristics. Compared to the class with transient AKI, the class that showed severe AKI with mild improvement but persistence had highest adjusted risks for developing AKD (OR 5.16; 95% CI 2.87-9.24) and composite 7-day outcome (HR 4.51; 95% CI 2.69-7.56). The class that demonstrated late mild AKI with persistence and worsening had highest risks for developing composite hospital discharge outcome (HR 2.04; 95% CI 1.41-2.94). These associations were similar on external validation., Conclusions: These 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging., (© 2024. The Author(s).)

Background: Acute kidney injury (AKI) is widespread in the intensive care unit (ICU) and affects patient prognosis. According to Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, the absolute and relative increases of serum creatinine (Scr) are classified into the same stage. Whether the prognosis of the two types of patients is similar in the ICU remains unclear., Methods: According to the absolute and relative increase of Scr, AKI stage 1 and stage 3 patients were divided into stage 1a and 1b, stage 3a and 3b groups, respectively. Their demographics, laboratory results, clinical characteristics, and outcomes were analyzed retrospectively., Results: Of the 345 eligible cases, we analyzed stage 1 because stage 3a group had only one patient. Using 53 or 61.88 µmol/L as the reference Scr (Scr ref ), no significant differences were observed in ICU mortality ( P 53 =0.076, P 61.88 =0.070) or renal replacement therapy (RRT) ratio, ( P 53 =0.356, P 61.88 =0.471) between stage 1a and 1b, but stage 1b had longer ICU length of stay (LOS) than stage 1a ( P 53 <0.001, P 61.88 =0.032). In the Kaplan-Meier survival analysis, no differences were observed in ICU mortality between stage 1a and 1b ( P 53 =0.378, P 61.88 =0.255). In a multivariate analysis, respiratory failure [HR = 4.462 (95% CI 1.144-17.401), p  = 0.031] and vasoactive drug therapy [HR = 4.023 (95% CI 1.584-10.216), p  = 0.003] were found to be independently associated with increased risk of death., Conclusion: ICU LOS benefit was more prominent in KDIGO SCr AKI stage 1a patients than in stage 1 b. Further prospective studies with a larger sample size are necessary to confirm the effectiveness of reclassification.

Rationale: Three consensus classifications of acute kidney injury have been published. These are RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease published by the Acute Dialysis Quality Initiative workgroup), AKIN (published by the Acute Kidney Injury Network ) and KDIGO (published by the Kidney Disease Improving Global Outcome workgroup). Acute kidney injury has been reported consistently as associated with worsened outcomes. However, toxicant-related acute kidney injury has been excluded from the studies used to validate the classifications of acute kidney injury., Objective: To study whether poisoned patients who develop acute kidney injury, as defined by consensus definitions/classifications, have higher mortality compared to those who did not., Methods: Databases were searched from 2004 to 2019 using the following keywords (KDIGO OR "Kidney Disease: Improving Global Outcomes" OR "Kidney Disease Improving Global Outcomes" OR AKIN OR "AKI network" OR "Acute kidney Injury Network" OR ADQI OR RIFLE OR "Acute dialysis quality initiative") AND (intoxication OR poisoning OR overdose OR ingestion) AND (AKI OR kidney OR renal OR ARF). If data were available, we used a random-effects meta-analysis model and Fisher's exact test to compare mortality in patients according to kidney function definitions (acute kidney injury vs not) and stages (stages vs no acute kidney injury), respectively. If data were available, we assessed the correlation between mortality and renal function (no acute kidney injury, risk/stage 1, injury/stage 2 and failure/stage 3) using the Spearman correlation. If available, we collected the results of statistical analyses in studies that have used acute kidney injury to predict mortality., Results: Study selection. Thirty-three relevant studies were found, 22/33 retrospective studies (67%) and 11/33 prospective studies (33%). Paraquat was the most frequent toxicant involved (13/33, 39%). We found a disparity between studies regarding the timeframe during which mortality was assessed, the temporality of the renal function considered to predict mortality (initial/worst) and the criteria used to define/grade acute kidney injury across studies. Univariate association between acute kidney injury definitions/stages and mortality. Consensus definitions/staging of acute kidney injury were associated with higher mortality, using univariate analyses, in twenty-eight (RIFLE = 7; AKIN = 12; KDIGO = 9) studies included but not in five (AKIN = 4, KDIGO = 1). When available data were pooled, RIFLE (5 studies), AKIN (16 studies) and KDIGO definitions (8 studies) of acute kidney injury were associated with a higher mortality (Log unadjusted Odds ratios [95%-confidence interval], 2.60 [2.23; 2.97], 2.02 [1.48; 2,52] and 3.22 [2,65; 3.78], respectively). However, we found high heterogeneity (I 2 =54,7%) and publication bias among studies using AKIN. In ten studies with available data, the correlation between renal function (no acute kidney injury, risk/stage 1, injury/stage 2, failure/stage 3) and mortality was significant in 5 studies (RIFLE = 2; AKIN = 3), but not in five studies (RIFLE = 1; AKIN = 3; KDIGO = 1). Multivariate association between acute kidney injury definitions/stages and mortality . The definitions of acute kidney injury were associated with higher mortality in two studies (RIFLE = 2), but not in four studies (AKIN = 1 and KDIGO = 3. The stages of acute kidney injury (including one or more stages) were associated with higher mortality in four (RIFLE = 1, AKIN = 1 and KDIGO = 2)., Conclusions: All three consensus definitions/classifications were associated independently with increased mortality in poisoning but with disparity between studies reporting acute kidney injury.

Over the past decade, new insights into epidemiology, pathophysiology and biomarkers have modified our understanding of acute kidney dysfunction and damage, and their association with subsequent chronic kidney disease. The concept of acute kidney injury (AKI), which has relied on established but nonetheless flawed biomarkers of solute clearance (serum creatinine levels and urinary output), has been challenged by the identification of novel biomarkers of tubular stress and/or damage. The expression of some of these novel biomarkers precedes changes in conventional biomarkers or can increase their predictive power, and might therefore enhance the clinical accuracy of the definition of AKI. In addition, the need to consider AKI recurrence, duration and progression to chronic kidney disease within the clinical and epidemiological framework of AKI led to the emergence of the concept of acute kidney disease. New definitions of acute syndromes of kidney impairment and injury are needed.

Objective: To evaluate whether extremely low gestational age neonates (ELGANs) randomized to erythropoietin have better or worse kidney-related outcomes during hospitalization and at 22-26 months of corrected gestational age (cGA) compared with those randomized to placebo., Study Design: We performed an ancillary study to a multicenter double-blind, placebo-controlled randomized clinical trial of erythropoietin in ELGANs., Results: The prevalence of severe (stage 2 or 3) acute kidney injury (AKI) was 18.2%. We did not find a statistically significant difference between those randomized to erythropoietin vs placebo for in-hospital primary (severe AKI) or secondary outcomes (any AKI and serum creatinine/cystatin C values at days 0, 7, 9, and 14). At 22-26 months of cGA, 16% of the cohort had an estimated glomerular filtration rate (eGFR) <90 mL/min/1.73 m 2 , 35.8% had urine albumin/creatinine ratio >30 mg/g, 23% had a systolic blood pressure (SBP) >95th percentile for age, and 40% had a diastolic blood pressure (DBP) >95th percentile for age. SBP >90th percentile occurred less often among recipients of erythropoietin (P < .04). This association remained even after controlling for gestational age, site, and sibship (aOR 0.6; 95% CI 0.39-0.92). We did not find statistically significant differences between treatment groups in eGFR, albumin/creatinine ratio, rates of SBP >95th percentile, or DBP >90th or >95th percentiles at the 2 year follow-up visit., Conclusions: ELGANs have high rates of in-hospital AKI and kidney-related problems at 22-26 months of cGA. Recombinant erythropoietin may protect ELGANs against long-term elevated SBP but does not appear to protect from AKI, low eGFR, albuminuria, or elevated DBP at 22-26 months of cGA., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Although the Kidney Disease: Improving Global Outcomes (KDIGO) criteria are used to define acute kidney injury, the criteria have limitations for including 2 different serum creatinine criteria in stage 1. We hypothesized that there would be differences in clinical outcomes between the 2 subgroups of stage 1 acute kidney injury in patients undergoing cardiac or thoracic aortic surgery., Methods: We reviewed 2510 cases. Patients with KDIGO stage 1 were divided into 2 subgroups (stage 1a: 0.3 mg/dL or greater of absolute increase in serum creatinine, n = 376; and stage 1b: 50% or greater relative increase, n = 365). Propensity score analysis was performed between stage 1a and 1b groups, yielding 240 pairs. We compared the length of hospital stay, the incidence of cardiovascular complications, 5-year all-cause mortality between these subgroups. Overall survival was compared between the subgroups after propensity score matching. We performed sensitivity analysis for Acute Kidney Injury Network (AKIN) criteria., Results: Length of hospital stay and 5-year all-cause mortality were worse in patients with KDIGO stage 1b compared with stage 1a. Five-year patient survival was significantly worse in patients with stage 1b compared with stage 1a after matching (log rank test, P = .002). We found similar results regarding AKIN criteria. Subgroup analysis showed that the significant difference in survival existed only when baseline serum creatinine was 0.8 mg/dL or greater., Conclusions: The KDIGO or AKIN criteria for stage 1 acute kidney injury could be further divided into 2 substages with different severity of clinical outcomes. These modified criteria could give additional prognostic information in patients undergoing cardiac or thoracic aortic surgery., (Copyright © 2021 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: Development of acute kidney injury (AKI) in invasively managed patients with acute coronary syndrome (ACS) is associated with a markedly increased mortality risk. Different definitions of AKI are in use, leading to varying prevalence and outcome measurements. The aim of the present study is to analyze an ACS population undergoing coronary angiography for differences in AKI prevalence and outcome using four established AKI definitions., Methods: 944 patients (30% female) were enrolled in a prospective registry between 2003 and 2005 with 6-month all-cause mortality as outcome measure. Four established AKI definitions were used: an increase in serum creatinine (sCR) ≥ 1.5 fold, ≥ 0.3 mg/dl, and ≥ 0.5 mg/dl and a decrease in eGFR > 25% from baseline (AKIN 1, AKIN 2, CIN, and RIFLE definition groups, respectively)., Results: AKI rates varied widely between the different groups. Using the CIN definition, AKI frequency was lowest (4.4%), whereas it was highest if the RIFLE definition was applied (13.2%). AKIN 2 displayed a twofold higher AKI prevalence compared with AKIN 1 (10.2% vs. 5.3% (p < 0.001)). AKI was a strong risk factor for mid-term mortality, with distinctive variability between the definitions. The lowest mortality risk was found in the RIFLE group (HR 6.0; 95% CI 3.7-10.0; p < 0.001), whereas CIN revealed the highest risk (HR 16.7; 95% CI 9.9-28.1; p < 0.001)., Conclusion: Prevalence and outcome in ACS patients varied considerably depending on the AKI definition applied. To define patients with highest renal function-associated mortality risk, use of the CIN definition seems to have the highest prognostic relevance.

Renal and immune systems maintain body homoeostasis during physiological fluctuations and following tissue injury. The immune system plays a central role during acute kidney injury (AKI), adapting evolutional systems programmed for host defence and minimizing unnecessary collateral damage. Indeed, depending upon the disease context, the impact of the immune system upon the manifestations and consequences of AKI can be quite different. Here we provide an overview of the known and unknown involvement of the immune system within the wide range of different forms of AKI, to oppose oversimplification and to endorse deeper insights into the pathogenesis of the different diseases causing kidney injury. This approach may help to overcome some of the current hurdles in translational AKI research and the development of specific treatments for the different diseases, all presenting with an acute increase in serum creatinine or decline in urinary output. One concept does not fit all., (© The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

Background and Objectives: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records., Design, Setting, Participants, & Measurements: We used the Medical Information Mart for Intensive Care III database, which consists of electronic health record data from intensive care units in a tertiary care hospital in the United States. We included patients ≥18 years with sepsis who developed AKI within 48 hours of intensive care unit admission. We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes were mortality 28 days after AKI and dialysis requirement., Results: We identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined features for K -means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 patients, and subphenotype 2 had 1898 patients, whereas subphenotype 3 had 660 patients. Subphenotype 1 had the lowest proportion of liver disease and lowest Simplified Acute Physiology Score II scores compared with subphenotypes 2 and 3. The proportions of patients with CKD were similar between subphenotypes 1 and 3 (15%) but highest in subphenotype 2 (21%). Subphenotype 1 had lower median bilirubin levels, aspartate aminotransferase, and alanine aminotransferase compared with subphenotypes 2 and 3. Patients in subphenotype 1 also had lower median lactate, lactate dehydrogenase, and white blood cell count than patients in subphenotypes 2 and 3. Subphenotype 1 also had lower creatinine and BUN than subphenotypes 2 and 3. Dialysis requirement was lowest in subphenotype 1 (4% versus 7% [subphenotype 2] versus 26% [subphenotype 3]). The mortality 28 days after AKI was lowest in subphenotype 1 (23% versus 35% [subphenotype 2] versus 49% [subphenotype 3]). After adjustment, the adjusted odds ratio for mortality for subphenotype 3, with subphenotype 1 as a reference, was 1.9 (95% confidence interval, 1.5 to 2.4)., Conclusions: Utilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes., (Copyright © 2020 by the American Society of Nephrology.)

Objectives: Risk prediction for postoperative acute kidney injury (AKI) has a great clinical value to achieve early prevention strategies for AKI after cardiac surgery. We aimed to identify the patients at risk of postoperative AKI and to create patient risk group for AKI using a simple risk estimation model in patients undergoing heart valve replacement surgery., Methods: Between May 2008 and February 2018, 219 consecutive patients undergoing heart valve replacement surgery with or without concomitant coronary artery bypass grafting (CAGB) were included in the study. To define postoperative AKI and its severity stages, KDIGO classification which is the latest uniform classification for determining and staging of AKI was used., Results: The AKI incidence was 38.8%, and Class I was the dominant stage (43.5%). Postoperative AKI development was associated with a serious of postoperative adverse events, early, and long-term mortality. Furthermore, the incidence of poor outcomes increased with the degree of AKI severity. The presence of older age, chronic obstructive pulmonary disease, NYHA class III-IV, diabetes, concomitant CABG, and longer cardiopulmonary bypass duration was found to be an independent predictor for AKI, and each factor was scored according to the integer value of their odds ratio, based on risk estimation model. Patient risk groups from mild to severe for AKI development were created. The patients at severe risk group exhibited a significantly higher rate of adverse events, early, and long-term mortality as well as lower long-term survival rates., Conclusions: The risk estimation model is a useful tool to identify the patients at risk and to create patient risk groups for postoperative AKI defined by KDIGO after heart valve replacement surgery.

Background: We previously identified two acute kidney injury (AKI) sub-phenotypes (AKI-SP1 and AKI-SP2) with different risk of poor clinical outcomes and response to vasopressor therapy. Plasma biomarkers of endothelial dysfunction (tumor necrosis factor receptor-1, angiopoietin-1 and 2) differentiated the AKI sub-phenotypes. However, it is unknown whether these biomarkers are simply markers or causal mediators in the development of AKI sub-phenotypes., Methods: We tested for associations between single-nucleotide polymorphisms within the Angiopoietin-1, Angiopoietin-2, and Tumor Necrosis Factor Receptor 1A genes and AKI- SP2 in 421 critically ill subjects of European ancestry. Top performing single-nucleotide polymorphisms (FDR < 0.05) were tested for cis-biomarker expression and whether genetic risk for AKI-SP2 is mediated through circulating biomarkers. We also completed in vitro studies using human kidney microvascular endothelial cells. Finally, we calculated the renal clearance of plasma biomarkers using 20 different timed urine collections., Results: A genetic variant, rs2920656C > T, near ANGPT2 was associated with reduced risk of AKI-SP2 (odds ratio, 0.45; 95% CI, 0.31-0.66; adjusted FDR = 0.003) and decreased plasma angiopoietin-2 (p = 0.002). Causal inference analysis showed that for each minor allele (T) the risk of developing AKI-SP2 decreases by 16%. Plasma angiopoietin-2 mediated 41.5% of the rs2920656 related risk for AKI-SP2. Human kidney microvascular endothelial cells carrying the T allele of rs2920656 produced numerically lower levels of angiopoietin-2 although this was not statistically significant (p = 0.07). Finally, analyses demonstrated that angiopoietin-2 is minimally renally cleared in critically ill subjects., Conclusion: Genetic mediation analysis provides supportive evidence that angiopoietin-2 plays a causal role in risk for AKI-SP2.

Despite progress in the supportive care available for critically ill patients, few advances have been made in the search for effective disease-modifying therapeutic options. The fact that many trials in critical care medicine have not identified a treatment benefit is probably due, in part, to the underlying heterogeneity of critical care syndromes. Numerous approaches have been proposed to divide populations of critically ill patients into more meaningful subgroups (subphenotypes), some of which might be more useful than others. Subclassification systems driven by clinical features and biomarkers have been proposed for acute respiratory distress syndrome, sepsis, acute kidney injury, and pancreatitis. Identifying the systems that are most useful and biologically meaningful could lead to a better understanding of the pathophysiology of critical care syndromes and the discovery of new treatment targets, and allow recruitment in future therapeutic trials to focus on predicted responders. This Review discusses proposed subphenotypes of critical illness syndromes and highlights the issues that will need to be addressed to translate subphenotypes into clinical practice., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: The timing of renal replacement therapy (RRT) for severe acute kidney injury is highly debated when no life-threatening complications are present. We assessed whether a strategy of delayed versus early RRT initiation affects 28-day survival in critically ill adults with severe acute kidney injury., Methods: In this systematic review and individual patient data meta-analysis, we searched MEDLINE (via PubMed), Embase, and the Cochrane Central Register of Controlled Trials for randomised trials published from April 1, 2008, to Dec 20, 2019, that compared delayed and early RRT initiation strategies in patients with severe acute kidney injury. Trials were eligible for inclusion if they included critically ill patients aged 18 years or older with acute kidney injury (defined as a Kidney Disease: Improving Global Outcomes [KDIGO] acute kidney injury stage 2 or 3, or, where KDIGO was unavailable, a renal Sequential Organ Failure Assessment score of 3 or higher). We contacted the principal investigator of each eligible trial to request individual patient data. From the included trials, any patients without acute kidney injury or who were not randomly allocated were not included in the individual patient data meta-analysis. The primary outcome was all-cause mortality at day 28 after randomisation. This study is registered with PROSPERO (CRD42019125025)., Findings: Among the 1031 studies identified, one study that met the eligibility criteria was excluded because the recruitment period was not recent enough, and ten (including 2143 patients) were included in the analysis. Individual patient data were available for nine studies (2083 patients), from which 1879 patients had severe acute kidney injury and were randomly allocated: 946 (50%) to the delayed RRT group and 933 (50%) to the early RRT group. 390 (42%) of 929 patients allocated to the delayed RRT group and who had available data did not receive RRT. The proportion of patients who died by day 28 did not significantly differ between the delayed RRT group (366 [44%] of 837) and the early RRT group (355 [43%] of 827; risk ratio 1·01 [95% CI 0·91 to 1·13], p=0·80), corresponding to an overall risk difference of 0·01 (95% CI -0·04 to 0·06). There was no heterogeneity across studies (I 2 =0%; τ 2 =0), and most studies had a low risk of bias., Interpretation: The timing of RRT initiation does not affect survival in critically ill patients with severe acute kidney injury in the absence of urgent indications for RRT. Delaying RRT initiation, with close patient monitoring, might lead to a reduced use of RRT, thereby saving health resources., Funding: None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Acute kidney injury (AKI) is a frequent and clinically relevant problem in critically ill patients. Various randomized controlled trials (RCT) have attempted to assess potentially beneficial treatments for AKI. Different approaches to applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria for AKI make a comparison of studies difficult. The objective of this study was to assess how different approaches may impact estimates of AKI incidence and whether the association between AKI and 90-day mortality varied by the approach used., Methods: Consecutive acutely admitted adult intensive care patients were included in a prospective observational study. AKI was determined following the KDIGO criteria during the first 7 days of ICU admission. In this post hoc analysis, we assessed whether AKI incidence differed when applying the KDIGO criteria in 30 different possible methods, varying in (A) serum creatinine (sCr), (B) urine output (UO), and (C) the method of combining these two into an outcome, e.g., severe AKI. We assessed point estimates and 95% confidence intervals for each incidence. Univariable regression was used to assess the associations between AKI and 90-day mortality., Results: A total of 1010 patients were included. Baseline creatinine was available in 449 (44%) patients. The incidence of any AKI ranged from 28% (95%CI 25-31%) to 75% (95%CI 72-77%) depending on the approach used. Methods to estimate missing baseline sCr caused a variation in AKI incidence up to 15%. Different methods of handling UO caused a variation of up to 35%. At 90 days, 263 patients (26%) had died, and all 30 variations were associated with 90-day mortality., Conclusions: In this cohort of critically ill patients, AKI incidence varied from 28 to 75%, depending on the method used of applying the KDIGO criteria. A tighter adherence to KDIGO definitions is warranted to decrease the heterogeneity of AKI and increase the comparability of future studies.

There have historically been concerns of acute kidney injury (AKI) with the use of aminoglycosides. The present study aimed to compare the AKI incidence and mortality rate between critically ill patients treated with aminoglycoside or meropenem in the intensive care unit setting using a propensity score matching approach. This cross-sectional study was conducted at two university hospitals from January 2011 to October 2017. Clinical and laboratorial data were evaluated to exclude potential confounders and to calculate the Charlson index. AKI was classified according to the Acute Kidney Injury Network criteria. All tests were two-tailed, and a p value ≤ 0.05 was considered significant in the univariate and multivariate analyses. We included 494 patients, 95 and 399 of whom used meropenem and aminoglycoside, respectively. Patients in the subgroup that used meropenem were matched with controls (aminoglycoside). Among the 494 patients, 120 developed any grade of AKI (24.2%). After propensity score matching, there were no significant differences in AKI incidence and mortality rate between the aminoglycoside and meropenem groups (p = 0.324 and 0.464, respectively). Patients on the aminoglycoside regimen neither presented a higher AKI incidence nor mortality rate when compared with those on the meropenem regimen. Aminoglycosides may be a safe option for the treatment of critically ill patients on carbapenem sparing antimicrobial stewardship programs.

Background: The long-term predictive ability of acute kidney injury (AKI) classification based on "Kidney Disease: Improving Global Outcomes"(KDIGO) AKI diagnosis criteria has not been clinically validated in diffuse proliferative lupus nephritis (DPLN) patients with AKI. Our objective was to assess the long-term predictive value of KDIGO AKI classification in DPLN patients with AKI., Methods: Retrospective cohort study was conducted by reviewing medical records of biopsy-proven DPLN patients with AKI from the First Affiliated Hospital of Wenzhou Medical University between Jan 1, 2000 and Dec 31, 2014. Multivariate Cox regression and survival analysis were performed., Results: One hundred sixty-seven DPLN patients were enrolled,82(49%) patients were normal renal function (No AKI), 40(24%) patients entered AKI-1 stage (AKI-1), 26(16%) patients entered AKI-2 stage (AKI-2) and 19(16%) patients entered AKI-3 stage (AKI-3). The mean follow-up of all patients was 5.1 ± 3.8 years. The patient survival without ESRD of all patients was 86% at 5 years and 79% at 10 years. The patient survival rate without ESRD at 10 yr was 94.5% for No AKI patients, 81.8% for AKI-1 patients, 44.9% for AKI-2 patients and 14.6% for AKI-3 patients. The area under the ROC curve for KDIGO AKI classification to predict the primary end point was 0.83 (95% CI: 0.73-0.93) (P < 0.001). In Cox regression analysis, AKI stage was independently associated with primary endpoint, with an adjusted hazard ratio (HR) of 3.8(95% CI 2.1-6.7, P < 0.001)., Conclusion: Severity of AKI based on KDIGO AKI category was associated with progression to ESRD in DPLN patients. Analytical data also confirmed the good discriminative power of the KDIGO AKI classification system for predicting long-term prognosis of DPLN patients with AKI.

Acute kidney injury (AKI) is the most common form of organ dysfunction occurring in patients admitted to the intensive care unit and contributes significantly to poor long-term outcomes. Despite this public health impact, no effective pharmacotherapy exists for AKI. One reason may be that heterogeneity is present within AKI as currently defined, thereby concealing unique pathophysiologic processes specific to certain AKI populations. Supporting this notion, we and others have shown that diversity within the AKI clinical syndrome exists, and the "one-size-fits-all" approach by current diagnostic guidelines may not be ideal. A "precision medicine" approach that exploits an individual's genetic, biologic, and clinical characteristics to identify AKI sub-phenotypes may overcome such limitations. Identification of AKI sub-phenotypes may address a critical unmet clinical need in AKI by (1) improving risk prognostication, (2) identifying novel pathophysiology, and (3) informing a patient's likelihood of responding to current therapeutics or establishing new therapeutic targets to prevent and treat AKI. This review discusses the current state of phenotyping AKI and future directions., (© 2020 S. Karger AG, Basel.)

Background: Mortality rates associated with acute kidney injury (AKI) vary among critically ill patients. Outcomes are often not corrected for severity or duration of AKI. Our objective was to analyse whether a new variable, AKI burden, would outperform 1) presence of AKI, 2) highest AKI stage, or 3) AKI duration in predicting 90-day mortality., Methods: Kidney Diseases: Improving Global Outcomes (KDIGO) criteria using creatinine, urine output and renal replacement therapy were used to diagnose AKI. AKI burden was defined as AKI stage multiplied with the number of days that each stage was present (maximum five), divided by the maximum possible score yielding a proportion. The AKI burden as a predictor of 90-day mortality was assessed in two independent cohorts (Finnish Acute Kidney Injury, FINNAKI and Simple Intensive Care Studies I, SICS-I) by comparing four multivariate logistic regression models that respectively incorporated either the presence of AKI, the highest AKI stage, the duration of AKI, or the AKI burden., Results: In the FINNAKI cohort 1096 of 2809 patients (39%) had AKI and 90-day mortality of the cohort was 23%. Median AKI burden was 0.17 (IQR 0.07-0.50), 1.0 being the maximum. The model including AKI burden (area under the receiver operator curve (AUROC) 0.78, 0.76-0.80) outperformed the models using AKI presence (AUROC 0.77, 0.75-0.79, p = 0.026) or AKI severity (AUROC 0.77, 0.75-0.79, p = 0.012), but not AKI duration (AUROC 0.77, 0.75-0.79, p = 0.06). In the SICS-I, 603 of 1075 patients (56%) had AKI and 90-day mortality was 28%. Median AKI burden was 0.19 (IQR 0.08-0.46). The model using AKI burden performed better (AUROC 0.77, 0.74-0.80) than the models using AKI presence (AUROC 0.75, 0.71-0.78, p = 0.001), AKI severity (AUROC 0.76, 0.72-0.79. p = 0.008) or AKI duration (AUROC 0.76, 0.73-0.79, p = 0.009)., Conclusion: AKI burden, which appreciates both severity and duration of AKI, was superior to using only presence or the highest stage of AKI in predicting 90-day mortality. Using AKI burden or other more granular methods may be helpful in future epidemiological studies of AKI.

Background: Acute kidney injury (AKI) is common in patients in the intensive care unit (ICU) and may be present on admission or develop during ICU stay. Our objectives were (a) to identify factors independently associated with the development of new AKI during early stay in the ICU and (b) to determine the risk factors for non-recovery of AKI., Methods: We retrospectively analysed prospectively collected data of patients admitted to a multi-disciplinary ICU in a single tertiary care centre in the UK between January 2014 and December 2016. We identified all patients without AKI or end-stage renal failure on admission to the ICU and compared the outcome and characteristics of patients who developed AKI according to KDIGO criteria after 24 h in the ICU with those who did not develop AKI in the first 7 days in the ICU. Multivariable logistic regression was applied to identify factors associated with the development of new AKI during the 24-72-h period after admission. Among the patients with new AKI, we identified those with full, partial or no renal recovery and assessed factors associated with non-recovery., Results: Among 2525 patients without AKI on admission, the incidence of early ICU-acquired AKI was 33.2% (AKI I 41.2%, AKI II 35%, AKI III 23.4%). Body mass index, Sequential Organ Failure Assessment score on admission, chronic kidney disease (CKD) and cumulative fluid balance (FB) were independently associated with the new development of AKI. By day 7, 69% had fully recovered renal function, 8% had partial recovery and 23% had no renal recovery. Hospital mortality was significantly higher in those without renal recovery. Mechanical ventilation, diuretic use, AKI stage III, CKD, net FB on first day of AKI and cumulative FB 48 h later were independently associated with non-recovery with cumulative fluid balance having a U-shape association., Conclusions: Early development of AKI in the ICU is common and mortality is highest in patients who do not recover renal function. Extreme negative and positive FB were strong risk factors for AKI non-recovery.

BACKGROUND Atypical hemolytic uremic syndrome (aHUS) is a genetic disorder with uncontrolled complement activation leading to systemic thrombotic microangiopathy; kidneys are almost invariably involved. Eculizumab has dramatically improved the prognosis of aHUS and affected women in the childbearing age are more likely to consider pregnancy, even if this could represent a risk for disease reactivation. Pregnancies in women with aHUS during Eculizumab treatment have been reported, with no cases of aHUS relapse. CASE REPORT We report the case of a female patient affected by aHUS with no specific gene mutations who had a pregnancy-associated aHUS relapse at 26-weeks of gestation during maintenance Eculizumab treatment. The patient developed stage II acute kidney injury and microangiopathic hemolytic anemia. Delivery by cesarean section at week 27, plasma exchange sessions and several supplemental Eculizumab administrations were required. After appropriate treatment, the patient partially recovered kidney function; the baby had a prolonged stay in the intensive care unit and showed no signs of neurologic damage. CONCLUSIONS Previous reports indicated that pregnancy-related aHUS relapses were unlikely in women undergoing Eculizumab treatment. Based on our case, we suggest caution in counselling pregnancy in women with aHUS treated with Eculizumab, especially in the absence of pathogenic mutations in complement-regulating genes. Clinicians should be aware of possible aHUS relapse in pregnancy during Eculizumab treatment.

Background: The first FDA-approved test to assess risk for acute kidney injury (AKI), [TIMP-2]•[IGFBP7], is clinically available in many parts of the world, including the USA and Europe. We sought to understand how the test is currently being used clinically., Methods: We invited a group of experts knowledgeable on the utility of this test for kidney injury to a panel discussion regarding the appropriate use of the test. Specifically, we wanted to identify which patients would be appropriate for testing, how the results are interpreted, and what actions would be taken based on the results of the test. We used a modified Delphi method to prioritize specific populations for testing and actions based on biomarker test results. No attempt was made to evaluate the evidence in support of various actions however., Results: Our results indicate that clinical experts have developed similar practice patterns for use of the [TIMP-2]•[IGFBP7] test in Europe and North America. Patients undergoing major surgery (both cardiac and non-cardiac), those who were hemodynamically unstable, or those with sepsis appear to be priority patient populations for testing kidney stress. It was agreed that, in patients who tested positive, management of potentially nephrotoxic drugs and fluids would be a priority. Patients who tested negative may be candidates for "fast-track" protocols., Conclusion: In the experience of our expert panel, biomarker testing has been a priority after major surgery, hemodynamic instability, or sepsis. Our panel members reported that a positive test prompts management of nephrotoxic drugs as well as fluids, while patients with negative results are considered to be excellent candidates for "fast-track" protocols.

Purpose: To assess the predictive validity of a modified Sequential Organ Failure Assessment (SOFA) score, of which the renal component was replaced with Kidney Disease Improving Global Outcomes (KDIGO) classification of Acute Kidney Injury (AKI)., Materials and Methods: Using a prospective cohort study on AKI in Japan, we replaced the renal component of SOFA score with AKI stages according to the KDIGO criteria except that initiation of renal replacement therapy was assigned four points. We assessed the predictive validity of KDIGO-based SOFA score for hospital and ICU mortality by comparing the areas under the receiver operating characteristic curve (AUC) derived from logistic regression models with that of the original SOFA score., Results: 2292 patients were registered. Overall hospital mortality was 11.6%, and ICU mortality was 5.1%. KDIGO-based SOFA score was moderately correlated with APACHE II score (rho = 0.476). The AUC for hospital and ICU mortality of KDIGO-based and the original SOFA score were 0.749 vs 0.745 (p = .393) and 0.790 vs 0.791 (p = .900)., Conclusions: The prognostic performance of KDIGO-based SOFA score was not superior but comparable to that of the original SOFA score., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: To generate a core set of items to develop classification criteria for scleroderma renal crisis (SRC) using consensus methodology., Methods: An international, multidisciplinary panel of experts was invited to participate in a 3-round Delphi exercise developed using a survey based on items identified by a scoping review. In round 1, participants were asked to identify omissions and clarify ambiguities regarding the items in the survey. In round 2, participants were asked to rate the validity and feasibility of the items using Likert-type scales ranging from 1 to 9 (where 1 = very invalid/unfeasible, 5 = uncertain, and 9 = very valid/feasible). In round 3, participants reviewed the results and comments from round 2 and were asked to provide final ratings. Items rated as highly valid and feasible (median scores ≥7 for each) in round 3 were selected as the provisional core set of items. A consensus meeting using a nominal group technique was conducted to further reduce the core set of items., Results: Ninety-nine experts from 16 countries participated in the Delphi exercise. Of the 31 items in the survey, consensus was achieved on 13, in the categories hypertension, renal insufficiency, proteinuria, and hemolysis. Eleven experts took part in the nominal group technique discussion, where consensus was achieved in 5 domains: blood pressure, acute kidney injury, microangiopathic hemolytic anemia, target organ dysfunction, and renal histopathology., Conclusion: A core set of items that characterize SRC was identified using consensus methodology. This core set will be used in future data-driven phases of this project to develop classification criteria for SRC., (© 2019, American College of Rheumatology.)

Objective: To develop and validate a prediction model of acute kidney injury (AKI) of any severity that could be used for AKI surveillance and management to improve clinical outcomes., Patients and Methods: This retrospective cohort study was conducted in medical, surgical, and mixed intensive care units (ICUs) at Mayo Clinic in Rochester, Minnesota, including adult (≥18 years of age) ICU-unique patients admitted between October 1, 2004, and April 30, 2011. Our primary objective was prediction of AKI using extant clinical data following ICU admission. We used random forest classification to provide continuous AKI risk score., Results: We included 4572 and 1958 patients in the training and validation mutually exclusive cohorts, respectively. Acute kidney injury occurred in 1355 patients (30%) in the training cohort and 580 (30%) in the validation cohort. We incorporated known AKI risk factors and routinely measured vital characteristics and laboratory results. The model was run throughout ICU admission every 15 minutes and achieved an area under the receiver operating characteristic curve of 0.88 on validation. It was 92% sensitive and 68% specific and detected 30% of AKI cases at least 6 hours before the criterion standard time (AKI stages 1-3). For discrimination of AKI stages 2 to 3, the model had 91% sensitivity, 71% specificity, and 53% detection of AKI cases at least 6 hours before AKI onset., Conclusion: We developed and validated an AKI prediction model using random forest for continuous monitoring of ICU patients. This model could be used to identify high-risk patients for preventive measures or identifying patients of prospective interventional trials., (Copyright © 2019 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

The 2012 Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guideline classifies acute kidney injury (AKI) into 3 stages defined by serum creatinine elevation or urine output decline. We evaluated the potential impact of further categorizing AKI stage 1 into two stages based on serum creatinine criteria, with a focus on how the resulting 4-stage classification would affect the association of AKI stages with clinical outcomes. We defined AKI stage 1a as an absolute increase in serum creatinine of 0.3 mg/dl within 48 hours and stage 1b as a 50% relative increase in serum creatinine within 7 days. We screened all admissions to 5 hospitals from 2012 to 2014 using standardized inclusion and exclusion criteria and included 81,651 admissions in this retrospective cohort study. The incidence of in-hospital AKI was 7.5% for stage 1a, 4.9% for stage 1b, 1.5% for stage 2, and 0.9% for stage 3. Length of stay following the first incidence of AKI was 3.9 days for stage 1a, 6.2 days for stage 1b, 8.8 days for stage 2, and 12.0 days for stage 3. Compared to patients with no AKI, the odds of in-hospital mortality were progressively higher for patients with higher AKI stages (odds ratio 4.3 for patients with stage 1a, 10.9 for stage 1b, 40.6 for stage 2, and 60.0 for stage 3 AKI). Patients with AKI stages 1a and 1b experienced clinically meaningful and statistically significant differences in length of stay and mortality. This study suggests that a modified 4-stage version of the KDIGO AKI classification may provide additional prognostic information., (Copyright © 2019 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

The acute renal failure is common in the hospitalized patients with the incidence is increasing. This results from the aging of the population and the widespread use of nephrotoxic therapies or diagnostic techniques. The acute renal failure is associated with an increased length of stay in hospital and the short and long-term mortality. The most common histological injury is the acute tubular necrosis. Although the most of acute renal failure is recovering, recent works have shown that there is a strong association between an acute renal failure and the increased risk of developing a chronic kidney disease., (Copyright © 2018 Société francophone de néphrologie, dialyse et transplantation. Published by Elsevier Masson SAS. All rights reserved.)

Acute kidney injury (AKI) is a frequent complication of hospitalization and is associated with an increased risk of chronic kidney disease (CKD), end-stage renal disease (ESRD), and mortality. While AKI is a known risk factor for short-term adverse outcomes, more recent data suggest that the risk of mortality and renal dysfunction extends far beyond hospital discharge. However, determining whether this risk applies to all patients who experience an episode of AKI is difficult. The magnitude of this risk seems highly dependent on the presence of comorbid conditions, including cardiovascular disease, hypertension, diabetes mellitus, preexisting CKD, and renal recovery. Furthermore, these comorbidities themselves lead to structural renal damage due to multiple pathophysiological changes, including glomeruloscleroses and tubulointerstitial fibrosis, which can lead to the loss of residual capacity, glomerular hyperfiltration, and continued deterioration of renal function. AKI seems to accelerate this deterioration and increase the risk of death, CDK, and ESRD in most vulnerable patients. Therefore, we strongly advocate adequate hemodynamic monitoring and follow-up in patients susceptible to renal dysfunction. Additionally, other potential renal stressors, including nephrotoxic medications and iodine-containing contrast fluids, should be avoided. Unfortunately, therapeutic interventions are not yet available. Additional research is warranted and should focus on the prevention of AKI, identification of therapeutic targets, and provision of adequate follow-up to those who survive an episode of AKI.

Sepsis is defined as organ dysfunction resulting from the host's deleterious response to infection. One of the most common organs affected is the kidneys, resulting in sepsis associated acute kidney injury (SA-AKI) that contributes to the morbidity and mortality of sepsis. A growing body of knowledge has illuminated the clinical risk factors, pathobiology, response to treatment, and elements of renal recovery that have advanced our ability to prevent, detect, and treat SA-AKI. Despite these advances, SA-AKI remains an important concern and clinical burden, and further study is needed to reduce the acute and chronic consequences. This review summarizes the relevant evidence, with a focus on the risk factors, early recognition and diagnosis, treatment, and long term consequences of SA-AKI. In addition to literature pertaining to SA-AKI specifically, pertinent sepsis and acute kidney injury literature relevant to SA-AKI was included., Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and declare the following interests: JLK has received consulting fees from Astute Medical, Sphingotec, and Pfizer and research fees from Astute Medical, Bioporto, NxStage Medical, and Satellite Healthcare for work in biomarkers of AKI, not specific to SA-AKI., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Introduction: Fulfillment of the diagnostic criteria for -hepatorenal syndrome type 1 (HRS-1) requires prior failure of 2 days of intravenous volume expansion and/or diuretic withdrawal. However, no parameter of volume status is used to guide the need for volume expansion in patients with suspected HRS-1. We hypothesized that point-of-care echocardiography (POCE) may better characterize the volume status in patients with acute kidney injury (AKI) and cirrhosis to ascertain or disprove the diagnosis of HRS-1., Methods: A pilot observational study was conducted to determine the clinical utility of POCE-based examination of inferior vena cava diameter (IVCD) and collapsibility index (IVCCI) to assess intravascular volume status in patients with cirrhosis and AKI who had been deemed adequately volume-repleted and thereby assigned a clinical diagnosis of HRS-1. Early improvement in kidney function was defined as ≥20% decrease in serum creatinine (sCr) at 48-72 h., Results: A total of 53 patients were included. The mean sCr at the time of volume assessment was 3.2 ± 1.5 mg/dL, and the mean Model for End-Stage Liver Disease score was 29 ± 8. Fifteen (23%) patients had an IVCD <1.3 cm and IVCCI >40% and were reclassified as fluid-depleted, 11 (21%) had an IVCD >2 cm and IVCCI <40% and were reclassified as fluid-expanded, and 8 (15%) had and IVCD <1.3 cm and IVCCI <40% and were reclassified as having intra-abdominal hypertension (IAH). Twelve (23%) patients exhibited early improvement in kidney function following a POCE-guided therapeutic maneuver, that is, volume expansion, diuresis, or paracentesis for those deemed fluid-depleted, fluid-expanded or having IAH, respectively., Conclusion: POCE-based assessment of volume status in cirrhotic individuals with AKI reveals marked heterogeneity. Unguided volume expansion in these patients may lead to premature or delayed diagnosis of HRS-1., (© 2019 S. Karger AG, Basel.)

Background: Researchers have suggested models to predict the risk of postoperative AKI (PO-AKI), but an externally validated risk index that can be practically implemented before patients undergo noncardiac surgery is needed., Methods: We performed a retrospective observational study of patients without preexisting renal failure who underwent a noncardiac operation (≥1 hour) at two tertiary hospitals in Korea. We fitted a proportional odds model for an ordinal outcome consisting of three categories: critical AKI (defined as Kidney Disease Improving Global Outcomes AKI stage ≥2, post-AKI death, or dialysis within 90 days after surgery), low-stage AKI (defined as PO-AKI events not fulfilling the definition of critical AKI), and no PO-AKI., Results: The study included 51,041 patients in a discovery cohort and 39,764 patients in a validation cohort. The Simple Postoperative AKI Risk (SPARK) index included a summation of the integer scores of the following variables: age, sex, expected surgery duration, emergency operation, diabetes mellitus, use of renin-angiotensin-aldosterone inhibitors, baseline eGFR, dipstick albuminuria hypoalbuminemia, anemia, and hyponatremia. The model calibration plot showed tolerable distribution of observed and predicted probabilities in both cohorts. The discrimination power of the SPARK index was acceptable in both the discovery (c-statistic 0.80) and validation (c-statistic 0.72) cohorts. When four SPARK classes were defined on the basis of the sum of the risk scores, the SPARK index and classes fairly reflected the risks of PO-AKI and critical AKI., Conclusions: Clinicians may consider implementing the SPARK index and classifications to stratify patients' PO-AKI risks before performing noncardiac surgery., (Copyright © 2019 by the American Society of Nephrology.)

Introduction: Acute kidney injury (AKI) is a common and devastating complication in patients with cirrhosis. In 2015, the International Club of Ascites (ICA) proposed the definition of hepatorenal syndrome (HRS) type of AKI (HRS-AKI) in patients with cirrhosis. This study aims to evaluate the criteria of HRS-AKI in patients with cirrhosis admitted to ICU with regard to the prognosis., Methods: A total of 349 cirrhotic patients consecutively admitted to intensive care unit (ICU) from 2010 to 2017 were retrospectively analyzed. Demographic parameters and clinical variables were collected with case report forms. The occurrence of AKI was determined according to ICA-AKI criteria. The phenotypes of AKI comprised pre-renal azotemia (PRA), acute tubular necrosis (ATN) and HRS. In our study, patients with PRA or ATN were classified to the non-HRS-AKI group., Results: The incidence of AKI was 73.0%, comprising PRA (18.6%), ATN (16.3%) and HRS (38.1%). The overall hospital mortality was 64.5%. Patients with AKI had a significantly higher in-hospital (76.1%) and 180-d (86.7%) mortality. AKI type was an independent risk factor for in-hospital mortality by a multivariate logistic regression. The in-hospital and 180-d mortality rates were of no significant difference among patients with HRS-AKI stages 1-3., Conclusions: AKI is common in patients with cirrhosis admitted to ICU, associated with significant in-hospital mortality. HRS-AKI was the most common and severe type of AKI in patients with cirrhosis admitted to ICU. The current staging system may not be applicable for HRS-AKI in patients with cirrhosis admitted to ICU.

Background: Research on acute kidney injury (AKI) has focused on identifying early biomarkers. However, whether AKI could be diagnosed in the absence of the classic signs of clinical AKI and whether the condition of subclinical AKI, identified by damage or functional biomarkers in the absence of oliguria or increased serum creatinine (sCr) levels, is clinically significant remains to be elucidated in critically ill children. The aims of the study were to investigate the associations between urinary cystatin C (uCysC) levels and AKI and mortality and to determine whether uCysC-positive subclinical AKI is associated with adverse outcomes in critically ill neonates and children., Methods: In this prospective cohort study, uCysC levels were serially measured during the first week after intensive care unit (ICU) admission in a heterogeneous group of patients (n = 510) presenting to a tertiary neonatal and pediatric ICU. The diagnosis of neonatal AKI that developed during the first week after admission was based on neonatal KDIGO criteria or sCr >1.5 mg/dL, and pediatric AKI was based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. The term "uCysC(-)" or "uCysC(+)", indicating the absence or presence of tubular injury, was defined by the optimal peak uCysC cutoff value for predicting ICU mortality., Results: The initial and peak uCysC levels were significantly associated with AKI and mortality, and had an area under the receiver operating characteristic curve of 0.76 and 0.81, respectively, for predicting mortality. At the optimal cutoff value of 1260 ng/mg uCr, the peak uCysC displayed sensitivity of 79.2% and specificity of 72.3% for predicting mortality. Among all patients, 130 (25.5%) developed uCysC(+)/AKI(-) status during the first week after admission. The adjusted odds ratio for patients with uCysC(+)/AKI(-) status in association with an increased risk of mortality compared with that for patients with uCysC(-)/AKI(-) was 9.34 (P < 0.001). Patients with uCysC(+)/AKI(-) spent 2.8 times as long in the ICU as those with uCysC(-)/AKI(-) (P < 0.001)., Conclusions: Both initial and peak uCysC levels are associated with AKI and mortality and are independently predictive of mortality in critically ill neonates and children. Subclinical AKI may occur without detectable loss of kidney function, and uCysC-positive subclinical AKI is associated with worse clinical outcomes in this population.

Hepatorenal syndrome (HRS) is a form of kidney function impairment that characteristically occurs in cirrhosis. Recent changes in terminology have led to acute HRS being referred to as acute kidney injury (AKI)-HRS and chronic HRS as chronic kidney disease (CKD)-HRS. AKI-HRS is characterized by a severe impairment of kidney function owing to vasoconstriction of the renal arteries in the absence of substantial abnormalities in kidney histology. Pathogenetic mechanisms involve disturbances in circulatory function due to a marked splanchnic arterial vasodilation, which triggers the activation of vasoconstrictor factors. An intense systemic inflammatory reaction that is characteristic of advanced cirrhosis may also be involved. The main triggering factors of AKI-HRS are bacterial infections, particularly spontaneous bacterial peritonitis. The diagnosis of AKI-HRS is a challenge because of a lack of specific diagnostic tools and mainly involves the differential diagnosis from other forms of AKI, particularly acute tubular necrosis. The prognosis of patients with AKI-HRS is poor, with a median survival of ≤3 months. The ideal treatment for AKI-HRS is liver transplantation in patients without contraindications. Medical therapy consists of vasoconstrictor drugs to counteract splanchnic arterial vasodilation together with volume expansion with albumin. Effective measures to prevent AKI-HRS include early identification and treatment of bacterial infections and the administration of albumin in patients with spontaneous bacterial peritonitis.

Objectives: Cardiac surgery-associated acute kidney injury is common in children and associates with negative outcomes. Novel interventions to reduce cardiac surgery-associated acute kidney injury require knowledge of its pathophysiology. States of altered perfusion, oxygen delivery, and energy consumption occur during cardiopulmonary bypass and could protect against or contribute to renal cellular injury and recovery. Near-infrared spectroscopy is noninvasive technology for monitoring regional blood flow and tissue oxygenation. This study evaluated the relationship between renal regional oxygen saturation and cardiac surgery-associated acute kidney injury, using near-infrared spectroscopy monitoring before, during, and after cardiopulmonary bypass in children., Design: Prospective cohort study., Setting: Single-center, tertiary care pediatric hospital (Stollery Children's Hospital, Edmonton, AB, Canada)., Patients: Children less than or equal to 10 kg undergoing congenital heart disease repair with cardiopulmonary bypass. Heart transplant, preoperative dialysis, sepsis, extracorporeal life support, congenital renal disease, and preoperative nephrotoxins were exclusions., Interventions: Renal regional near-infrared spectroscopy monitoring before, during, and after cardiopulmonary bypass., Measurements and Main Results: Outcome measure was cardiac surgery-associated acute kidney injury (defined according to Kidney Disease: Improving Global Outcomes criteria). Regional oxygen saturation was measured continuously using near-infrared spectroscopy (INVOS 5100C Cerebral/Somatic Oximeter; Medronic, Troy, MI) from time of anesthesia to time of transfer to intensive care. Cardiac surgery-associated acute kidney injury occurred in 65%. Lower baseline (precardiopulmonary bypass) regional oxygen saturation was associated with decreased risk of cardiac surgery-associated acute kidney injury (p = 0.01); children with baseline regional oxygen saturation in the highest tertile were 7.14 times more likely to get cardiac surgery- associated acute kidney injury (vs lowest tertile). Area under the curve for ability of baseline regional oxygen saturation to predict cardiac surgery-associated acute kidney injury was 0.73 (95% CI, 0.60-0.85). Children with lower baseline glomerular filtration rate had lower mean renal regional oxygen saturation., Conclusions: Findings demonstrate that preoperative oxygen supply/demand balance is an important predictor of cardiac surgery-associated acute kidney injury, suggesting lower preoperative (and intraoperative) renal blood flow may be protective. There is not yet a definite link between remote ischemic preconditioning and prevention of cardiac surgery-associated acute kidney injury; however, renal protective effects of sublethal ischemia should continue to be explored.

The aim of this study was to validate Acute Kidney Injury Network (AKIN) and to develop a modified AKIN aimed at an improved classification of patients without baseline creatinine versus Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease (RIFLE) in general intensive care unit (ICU) patients.We retrospectively analyzed medical records of general ICU patients over a 1-year period. We compared the grading of severity as well as the prediction of mortality and renal replacement therapy by AKIN and RIFLE. Furthermore, a modified AKIN score was evaluated.A total of 321 patients were included. In 87% of cases, the 2 definitions classified patients in the concordant severity group. Higher scores of AKIN and RIFLE were associated with increased ICU- and 28-day mortality. Both definitions provided large receiver operating characteristics (ROC)-area under the curve (AUCs) for the prediction of mortality, which were comparable to the ROC-AUC of unclassified serum creatinine. Modification of the AKIN score with a "backward classification" of baseline creatinine based on its time course resulted in a higher AKIN score in 32 patients.RIFLE and AKIN definitions had a high concordance in staging the severity of acute kidney injury. There was a strong relationship between the stages and need for dialysis, ICU, and 28-day mortality. However, unclassified serum creatinine values were at least comparable. Standardized observation of the creatinine time course allows for "ex-post" AKIN-classification in a substantial number of patients with missing baseline creatinine values.

Background: The early prediction of acute kidney injury (AKI) can facilitate timely intervention and prevent complications. We aimed to understand the predictive value of urinary liver-type fatty-acid binding protein (L-FABP) levels on admission to medical (non-surgical) cardiac intensive care units (CICUs) for AKI, both independently and in combination with serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels., Methods: We prospectively investigated the predictive value of L-FABP and NT-proBNP for AKI in a large, heterogeneous cohort of patients treated in medical CICUs. Baseline urinary L-FABP and serum NT-proBNP were measured on admission. AKI was diagnosed according to the Kidney Disease: Improving Global Outcomes criteria. We studied 1273 patients (mean age, 68 years), among whom 46% had acute coronary syndromes, 38% had acute decompensated heart failure, 5% had arrhythmia, 3% had pulmonary hypertension, 2% had acute aortic syndrome, 2% had infective endocarditis, and 1% had Takotsubo cardiomyopathy., Results: Urinary L-FABP levels correlated with serum NT-proBNP levels (r = 0.17, p < 0.0001). AKI occurred in 224 patients (17.6%), including 48 patients with stage 2 or 3 disease. Patients who developed AKI had higher one-week and 6-month mortality than those who did not develop AKI (p = 0.0002 and p = 0.003, respectively). In the multivariate logistic analysis, both L-FABP (p < 0.0001) and NT-proBNP (p = 0.006) were independently associated with the development of AKI. Adding L-FABP and NT-proBNP to a baseline model that included established risk factors further improved reclassification (p < 0.001) and discrimination (p < 0.01) beyond that of the baseline model or any single biomarker individually., Conclusions: Urinary L-FABP and serum NT-proBNP levels on admission are independent predictors of AKI, and when used in combination, improve early prediction of AKI in patients hospitalized at medical CICUs.

Purpose: The aim of our study was to evaluate the effects of AKI development on mortality with four different classification systems (RIFLE, AKIN, CK, KDIGO) in critically ill trauma patients followed in the intensive care unit., Methods: A retrospective review of 2034 patients in our intensive care unit was conducted between July 2010 and August 2013. A total of 198 patients with primary trauma were included in the study to evaluate the development of AKI., Results: When the presence of AKI was investigated according to the four criteria (RIFLE, AKIN, CK, and KDIGO), the highest incidence of AKI was found according to the KDIGO classification (74.2%), followed by AKIN (72.2%), RIFLE (69.7%), and CK (59.1%). It was observed that more AKI developed according to KDIGO in patients with multiple trauma and thoracic trauma (p = 0.031, p = 0.029). Sixty-two (31%) of the 198 trauma patients monitored in the intensive care unit died; mortality was frequently found high in AKI stage 2 and 3 patients. According to the CK classification, there was a significant increase in mortality in patients with AKI on the first day (p = 0.045). AKI classifications by RIFLE, AKIN, CK, and KDIGO were independently associated with the risk of in-hospital death., Conclusion: In this study, the presence of AKI was found to be an independent risk factor in the development of in-hospital mortality according to all classification systems (RIFLE, AKIN, CK, and KDIGO) in critically traumatic patients followed in ICU, and the compatibility between RIFLE, AKIN, and KDIGO was the highest among the classification systems.

Background: Perioperative acute kidney injury (AKI) is an important predictor of long-term all-cause mortality after coronary artery bypass (CABG). However, the effect of AKI on long-term mortality after cardiac valve operations is hitherto undocumented., Methods: Perioperative renal injury and long-term all-cause mortality after valve operations were studied in a prospective cohort of patients undergoing solitary valve operations (n = 2,806) or valve operations combined with CABG (n = 1,260) with up to 18 years of follow-up. Postoperative serum creatinine increase was classified according to AKI staging 0 to 3. Patients undergoing solitary CABG (n = 4,938) with cardiopulmonary bypass served as reference., Results: In both valve and valve+CABG operations, postoperative renal injury of AKI stage 1 or higher was progressively associated with an increase in long-term mortality (hazard ratio [HR], 2.27, p < 0.05 for valve; HR, 1.65, p < 0.05 for valve+CABG; HR, 1.56, p < 0.05 for CABG). Notably, the mortality risk increased already substantially at serum creatinine increases of 10% to 25%-that is, far below the threshold for AKI stage 1 after valve operations (HR, 1.39, p < 0.05), but not after valve operations combined with CABG or CABG only., Conclusions: An increase in serum creatinine by more than 10% during the first week after valve operation is associated with an increased risk for long-term mortality after cardiac valve operation. Thus, AKI classification clearly underestimates long-term mortality risk in patients undergoing valve operations., (Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: In evidence-based medicine, multicenter, prospective, randomized controlled trials (RCTs) are the gold standard for evaluating treatment benefits and ensuring the effectiveness of interventions. Patient-centered outcomes, such as mortality, are most often the preferred evaluated outcomes. While there is currently agreement on how to classify renal dysfunction in critically ill patients , the application frequency of this new classification system in RCTs has not previously been evaluated. In this study, we aim to assess the definition of renal dysfunction in multicenter RCTs involving critically ill patients that included mortality as a primary endpoint., Methods: A comprehensive search was conducted for publications reporting multicenter randomized controlled trials (RCTs) involving adult patients in intensive care units (ICUs) that included mortality as a primary outcome. MEDLINE and PUBMED were queried for relevant articles in core clinical journals published between May 2004 and December 2017., Results: Of 418 articles reviewed, 46 multicenter RCTs with a primary endpoint related to mortality were included. Thirty-six (78.3%) of the trial reports provided information on renal function in the participants. Only seven articles (15.2%) included mean or median serum creatinine levels, mean creatinine clearance or estimated glomerular filtration rates. Sequential organ failure assessment (SOFA) score was the most commonly used definition of renal dysfunction (20 studies; 43.5%). Risk, Injury, Failure, Loss, End-stage renal disease (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease Improving Global Outcomes (KDIGO) criteria were used in five (10.9%) trials. In thirteen trials (28.3%), no renal dysfunction criteria were reported. Only one trial excluded patients with renal dysfunction, and it used urinary output or need for renal replacement therapy (RRT) as criteria for this diagnosis., Conclusion: The presence of renal dysfunction was included as a baseline patient characteristic in most RCTs. The RIFLE, AKIN and KDIGO classification systems were infrequently used; renal dysfunction was generally defined using the SOFA score.

Acute kidney injury (AKI) is a heterogeneous clinical syndrome that has multiple aetiologies, variable pathogenesis and diverse outcomes. However, these heterogeneities are not reflected in current approaches to the diagnosis and, to some degree, treatment of AKI. For example, congestive heart failure and dehydration can produce identical changes in serum creatinine level and urine output (parameters that are used to define AKI); however, they differ vastly in their physiological contexts and demand completely opposite treatments. AKI is often still considered to be a homogeneous clinical entity, which implies a uniform pathogenesis and a well-defined prognosis. As a consequence, efforts to find effective AKI treatments have been hampered by a lack of clear clinical classifications for various types of AKI. In addition, subclassification of AKI into subclinical phenotypes - for example, on the basis of protein biomarkers and other in vitro diagnostics that take into account disease aetiology and underlying pathogenesis - might be necessary to develop therapeutic approaches that effectively target the widely differing pathomechanisms of AKI. In this Review, we discuss the major subtypes of AKI that are associated with sepsis, major surgery, renal hypoperfusion and nephrotoxin exposure -situations that are typically seen in the intensive care setting. We consider differences and similarities in their phenotype, pathogenesis and outcomes and how this information might be used to guide treatment.

We assessed incidence, predictors, and impact on 6-month mortality of contrast-induced acute kidney injury (CI-AKI) after coronary angiography with or without percutaneous coronary intervention in patients with acute coronary syndrome (ACS), according to 3 different CI-AKI definitions. Serum creatinine (sCr) was assessed at baseline and 48 to 72 hours after procedure to classify patients into 3 CI-AKI groups: Group 1: increase in sCR ≥25% over baseline but absolute increase <0.5 mg/dl; Group 2: absolute increase ≥0.5 mg/dl; Group 3: absolute increase ≥0.3 mg/dl or ≥50% over baseline. The association between CI-AKI and all-cause 6-month mortality was assessed using multivariate Cox regression. Among 1,002 patients included, median age was 68 [57 to 79] years. The sample had the following characteristics: 70% men, 25% diabetics, 22% had a history of myocardial infarction, 21% had baseline estimated glomerular filtration rate (as calculated by the Modification of Diet in Renal Disease)  <60 ml/min/1.72 m 2 , 34% had ST-segment elevation myocardial infarction, 61% underwent percutaneous coronary intervention, and 43% had multivessel disease. Based on changes in sCr, 89 patients (8.9%) were classified in Group 1; 69 (6.9%) in Group 2; and 157 (15.7%) in Group 3, whereas sCr did not increase >25% in the remaining 844 (84.2%). CI-AKI was significantly associated with 6-month all-cause mortality using the definitions for Group 2 (hazard ratio 3.1, 95% confidence interval [CI] 1.5 to 6.6, p = 0.002) and Group 3 (hazard ratio 2.03, 95% CI 1.03 to 4.0, p = 0.04), but not Group 1. In conclusion, based on the definition used for CI-AKI, CI-AKI is observed in 6% to 15.7% of patients. An increase of 25% over baseline sCr does not identify high-risk patients. CI-AKI defined as an increase in sCr >0.3 mg/dl identifies 15.7% of the population at 2-fold higher risk of mortality., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The international classification of diseases (ICD) code is frequently used to identify renal impairment in epidemiological research. However, Australian studies examining accuracy of this administrative data in coding kidney injury are lacking., Aims: To compare the ICD 10 coding with the kidney disease: improving global outcomes (KDIGO) criteria in diagnosing acute kidney injury (AKI) and/or chronic kidney disease (CKD)., Methods: A retrospective study of 325 patients admitted to general medicine during January 2012 was performed. Sensitivity and specificity of ICD 10 in identifying AKI and CKD were calculated using KDIGO as gold standard., Results: The sensitivities of ICD 10 in identifying AKI and CKD were low for both (59.5% and 54.1%), but the specificities were high (86.2% and 90.2%). Using KDIGO criteria, we identified 72 AKI (22%), 56 CKD (17%), 64 AKI on CKD (19%) and 133 controls (40%). Compared to the control group, patients with AKI and AKI on CKD had longer length of stay (3.2 vs 4.9 days and 3.2 vs 4.8 days, P = 0.20). Renal impairment groups had increased in-hospital mortality rate (5% control, 6% AKI, 10% CKD, 9% AKI on CKD) and re-admission rate within 30 days (13% control, 20% AKI, 25% CKD, 26% AKI on CKD). After adjusting for age, gender and comorbidities, the difference in outcomes was not statistically significant., Conclusion: This study shows that ICD 10 fails to identify almost half of the patients with AKI (40.5%) and CKD (45.9%) in our cohort. A total of 60% had evidence of renal impairment as defined by KDIGO., (© 2017 The Authors. Internal Medicine Journal by Wiley Publishing Asia Pty Ltd on behalf of Royal Australasian College of Physicians.)

No therapies have been shown to improve outcomes in patients with acute kidney injury (AKI). Given the high morbidity and mortality associated with AKI this represents an important unmet medical need. A common feature of all of the therapeutic development efforts for AKI is that none were driven by target selection or preclinical modeling that was based primarily on human data. This is important when considering a heterogeneous and dynamic condition such as AKI, in which in the absence of more accurate molecular classifications, clinical cohorts are likely to include patients with different types of injury at different stages in the injury and repair continuum. The National Institutes of Health precision medicine initiative offers an opportunity to address this. By creating a molecular tissue atlas of AKI, defining patient subgroups, and identifying critical cells and pathways involved in human AKI, this initiative has the potential to transform our current approach to therapeutic discovery. In this review, we discuss the opportunities and challenges that this initiative presents, with a specific focus on AKI, what additional efforts will be needed to apply these discoveries to therapeutic development, and how we believe this effort might lead to the development of new therapeutics for subsets of patients with AKI., (Copyright © 2017. Published by Elsevier Inc.)