Genetic variation implicates plasma angiopoietin-2 in the development of acute kidney injury sub-phenotypes

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

INTRODUCTION

Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.

PATIENTS AND METHODS

This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.

RESULTS

Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.

CONCLUSIONS

Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit

BACKGROUND

Sepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output.

SUMMARY

Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI.

KEY MESSAGES

Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.

Predictive value of lactate dehydrogenase combined with the abbreviated burn severity index for acute kidney injury and mortality in severe burn patients

BACKGROUND

Extensive burns are devastating trauma. This study aimed to explore the predictive value of early lactate dehydrogenase (LDH) level, the abbreviated burn severity index (ABSI) and their combination on acute kidney injury (AKI) and mortality after severe burns.

METHODS AND RESULTS

194 severe burn patients (TBSA ≥ 30%) were included. After multivariate analyses, early LDH value (first 24 h after admission) was an independent risk factor for early AKI (OR=1.095, CI,1.025-1.169,p = 0.007) and AKI (OR=1.452, CI,1.131-1.864, p = 0.003) in severe burn patients and was still a significant risk factor for mortality (OR=1.059, CI,1.006-1.115，p = 0.03). In ROC analysis, after combining LDH and ABSI, the AUC values were 0.925 for AKI, 0.926 for stage 3 AKI, and 0.904 for mortality. Based on cut-off values, patients were divided into different risk groups. The cumulative incidence of AKI (within 5 days, 30 days) and survival rate (within 60 days) were analyzed by the Kaplan-Meier method. The mortality, AKI incidence, and AKI staging showed a significant upward trend with the increasing risk level (P < 0.001).

CONCLUSION

Early LDH level is an independent risk factor for early AKI and AKI. LDH combined with ABSI can better predict mortality and AKI than single indicators.

Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes

RATIONALE & OBJECTIVE

Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology, and outcomes. We incorporated plasma and urine biomarker measurements to identify AKI subgroups (subphenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes.

STUDY DESIGN

Multicenter cohort study.

SETTING & PARTICIPANTS

769 hospitalized adults with AKI matched with 769 without AKI, enrolled from December 2009 to February 2015 in the ASSESS-AKI Study.

PREDICTORS

29 clinical, plasma, and urinary biomarker parameters used to identify AKI subphenotypes.

OUTCOME

Composite of major adverse kidney events (MAKE) with a median follow-up period of 4.7 years.

ANALYTICAL APPROACH

Latent class analysis (LCA) and k-means clustering were applied to 29 clinical, plasma, and urinary biomarker parameters. Associations between AKI subphenotypes and MAKE were analyzed using Kaplan-Meier curves and Cox proportional hazard models.

RESULTS

Among 769 AKI patients both LCA and k-means identified 2 distinct AKI subphenotypes (classes 1 and 2). The long-term risk for MAKE was higher with class 2 (adjusted HR, 1.41 [95% CI, 1.08-1.84]; P=0.01) compared with class 1, adjusting for demographics, hospital level factors, and KDIGO stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of long-term chronic kidney disease progression and dialysis. The top variables that were different between classes 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury; serum creatinine ranked 20th out of the 29 variables for differentiating classes.

LIMITATIONS

A replication cohort with simultaneously collected blood and urine sampling in hospitalized adults with AKI and long-term outcomes was unavailable.

CONCLUSIONS

We identify 2 molecularly distinct AKI subphenotypes with differing risk of long-term outcomes, independent of the current criteria to risk stratify AKI. Future identification of AKI subphenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI.

PLAIN-LANGUAGE SUMMARY

Acute kidney injury (AKI) occurs commonly in hospitalized patients and is associated with high morbidity and mortality. The AKI definition lumps many different types of AKI together, but subgroups of AKI may be more tightly linked to the underlying biology and clinical outcomes. We used 29 different clinical, blood, and urinary biomarkers and applied 2 different statistical algorithms to identify AKI subtypes and their association with long-term outcomes. Both clustering algorithms identified 2 AKI subtypes with different risk of chronic kidney disease, independent of the serum creatinine concentrations (the current gold standard to determine severity of AKI). Identification of AKI subtypes may facilitate linking therapies to underlying biology to prevent long-term consequences after AKI.

Precision management of acute kidney injury in the intensive care unit: current state of the art

Acute kidney injury (AKI) is a prototypical example of a common syndrome in critical illness defined by consensus. The consensus definition for AKI, traditionally defined using only serum creatinine and urine output, was needed to standardize the description for epidemiology and to harmonize eligibility for clinical trials. However, AKI is not a simple disease, but rather a complex and multi-factorial syndrome characterized by a wide spectrum of pathobiology. AKI is now recognized to be comprised of numerous sub-phenotypes that can be discriminated through shared features such as etiology, prognosis, or common pathobiological mechanisms of injury and damage. The characterization of sub-phenotypes can serve to enable prognostic enrichment (i.e., identify subsets of patients more likely to share an outcome of interest) and predictive enrichment (identify subsets of patients more likely to respond favorably to a given therapy). Existing and emerging biomarkers will aid in discriminating sub-phenotypes of AKI, facilitate expansion of diagnostic criteria, and be leveraged to realize personalized approaches to management, particularly for recognizing treatment-responsive mechanisms (i.e., endotypes) and targets for intervention (i.e., treatable traits). Specific biomarkers (e.g., serum renin; olfactomedin 4 (OLFM4); interleukin (IL)-9) may further enable identification of pathobiological mechanisms to serve as treatment targets. However, even non-specific biomarkers of kidney injury (e.g., neutrophil gelatinase-associated lipocalin, NGAL; [tissue inhibitor of metalloproteinases 2, TIMP2]·[insulin like growth factor binding protein 7, IGFBP7]; kidney injury molecule 1, KIM-1) can direct greater precision management for specific sub-phenotypes of AKI. This review will summarize these evolving concepts and recent innovations in precision medicine approaches to the syndrome of AKI in critical illness, along with providing examples of how they can be leveraged to guide patient care.

Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup

Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients and is strongly associated with adverse outcomes, including an increased risk of chronic kidney disease, cardiovascular events and death. The pathophysiology of SA-AKI remains elusive, although microcirculatory dysfunction, cellular metabolic reprogramming and dysregulated inflammatory responses have been implicated in preclinical studies. SA-AKI is best defined as the occurrence of AKI within 7 days of sepsis onset (diagnosed according to Kidney Disease Improving Global Outcome criteria and Sepsis 3 criteria, respectively). Improving outcomes in SA-AKI is challenging, as patients can present with either clinical or subclinical AKI. Early identification of patients at risk of AKI, or at risk of progressing to severe and/or persistent AKI, is crucial to the timely initiation of adequate supportive measures, including limiting further insults to the kidney. Accordingly, the discovery of biomarkers associated with AKI that can aid in early diagnosis is an area of intensive investigation. Additionally, high-quality evidence on best-practice care of patients with AKI, sepsis and SA-AKI has continued to accrue. Although specific therapeutic options are limited, several clinical trials have evaluated the use of care bundles and extracorporeal techniques as potential therapeutic approaches. Here we provide graded recommendations for managing SA-AKI and highlight priorities for future research.

MICROVASCULAR ENDOTHELIAL ACTIVATION/DYSFUNCTION AND DYSREGULATION OF THE ANGIOPOIETIN-TIE2 SYSTEM IN THE PATHOGENESIS OF LIFE-THREATENING INFECTIONS

Microvascular endothelial activation/dysfunction has emerged as an important mechanistic pathophysiological process in the development of morbidity and mortality in life-threatening infections. The angiopoietin-Tie2 system plays an integral role in the regulation of microvascular endothelial integrity. Angiopoietin-1 (Ang-1), produced by platelets and pericytes, is the cognate agonistic ligand for Tie2, promoting endothelial quiescence and inhibiting microvascular leak. Angiopoietin-2 (Ang-2), released from activated endothelial cells in Weibel-Palade bodies, competes with Ang-1 for binding to Tie-2, thereby promoting endothelial activation/dysfunction and microvascular leak. In healthy homeostasis, levels of Ang-1 far exceed Ang-2 in circulating serum/plasma. In diseases associated with systemic inflammation, Ang-1 falls and Ang-2 rises (i.e., Ang-1/2 dysregulation). Our research has shown that Ang-1/2 dysregulation is a prominent feature in a number of life-threatening infections and critical illnesses, including sepsis, cerebral malaria, COVID-19, streptococcal toxic shock syndrome (STSS), hemolytic-uremic syndrome (HUS), dengue, and CAR T-cell-associated neurotoxicity. Further work has implicated Ang-1/2 dysregulation in the development of end-organ injury, including acute lung injury/ARDS, acute kidney injury (AKI), and blood-brain-barrier (BBB) breakdown. Current studies are focused in three areas: (a) translation of Ang-1 and -2 as clinically informative prognostic and "theranostic" biomarkers in critically ill individuals; (b) incorporation of Ang-1/2 assays in a point of care device for clinical triage decision making; and (c) development of an engineered Ang-1 super agonist nanoparticle as a novel pathogen-agnostic therapeutic to prevent and/or mitigate end-organ dysfunction in individuals with life-threatening infections and critical illnesses associated with systemic inflammation.

Assessment of Angiopoietin-2 Single Nucleotide Polymorphism in Patients with Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that destroys joint cartilage and causes disability. Synovial inflammation, with angiogenesis, is an early event in the progression of the disease. Angiopoietin 2 (ANGPT2) is a cytokine with both inflammatory and angiogenic effects. Many genes can influence RA susceptibility and disease activity. The aim is to assess the relationship between ANGPT2 gene polymorphism (rs3020221) and RA. The study was a case-control study that included 212 RA patients and 238 age-and gender-matched healthy volunteers. RA disease activity was assessed using the Disease Activity Score 28 index. Erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, and antibody to cyclic citrullinated peptide were measured. ANGPT2 rs3020221 C > T SNP genotyping was done using real-time polymerase chain reaction (PCR). The TT genotype was more frequently represented in RA patients than in healthy controls (18.9% and 7.1%, respectively, p < 0.001) and increased the chance of developing RA four-fold, as compared to other genotypes (OR = 4.00, 95% CI = 2.09-7.63) (p < 0.001). The CT genotype was associated with elevated levels of the inflammatory markers ESR and CRP in RA patients (p = 0.012 and 0.037, respectively) as well as the DAS28 ESR Score (p < 0.001). The presence of the T allele either under the dominant model (for genotypes CT and TT) or the recessive model (for the genotype TT) predicts RA disease. Assessment of ANGPT2 gene polymorphism is useful to predict the patients with susceptibility to RA. The presence of T allele increased the risk of developing RA disease by two folds.

Artificial Intelligence in Acute Kidney Injury Prediction

The use of artificial intelligence (AI) in nephrology and its associated clinical research is growing. Recent years have seen increased interest in utilizing AI to predict the development of hospital-based acute kidney injury (AKI). Several AI techniques have been employed to improve the ability to detect AKI across a variety of hospitalized settings. This review discusses the evolutions of AKI risk prediction discussing the static risk assessment models of yesteryear as well as the more recent trend toward AI and advanced learning techniques. We discuss the relative improvement in AKI detection as well as the relative dearth of data around the clinical implementation and patient outcomes using these models. The use of AI for AKI detection and clinical care is in its infancy, and this review describes how we arrived at our current position and hints at the promise of the future.

The impact of Angiopoietin-2 genetic polymorphisms on susceptibility for malignant breast neoplasms

Breast cancer causes morbidity and mortality among women worldwide, despite much research illuminating the genetic basis of this disease. Anti-angiogenesis therapies have been widely studied, although the association between angiopoietin-2 (ANGPT2) single nucleotide polymorphisms (SNPs) and breast cancer subtypes remains unclear. This case-control study included 464 patients with malignant breast neoplasms and 539 cancer-free females. We explored the effects of ANGPT2 SNPs on the susceptibility for a malignant breast neoplasm in a Chinese Han population. Five ANGPT2 SNPs (rs2442598, rs734701, rs1823375, 11,137,037, and rs12674822) were analyzed using TaqMan SNP genotyping. Carriers of the variant GG allele of rs1823375 were less likely than wild-type carriers to be diagnosed with clinically staged breast cancer, while females with human epidermal growth factor receptor 2 (HER2)-enriched disease carrying the CG or the CG+GG genotype at rs1823375 were significantly less likely than CC genotype carriers to be of lymph node status N1-N3. We also found that the T-T-C-A-T ANGPT2 haplotype significantly increased the risk for developing a malignant breast neoplasm by 1.385-fold (95% CI: 1.025-1.871; p < 0.05). Our study is the first to document a correlation between ANGPT2 polymorphisms and the development and progression of a malignant breast neoplasm in females of Chinese Han ethnicity.

Subphenotypes in acute kidney injury: a narrative review

Acute kidney injury (AKI) is a frequently encountered syndrome especially among the critically ill. Current diagnosis of AKI is based on acute deterioration of kidney function, indicated by an increase in creatinine and/or reduced urine output. However, this syndromic definition encompasses a wide variety of distinct clinical features, varying pathophysiology, etiology and risk factors, and finally very different short- and long-term outcomes. Lumping all AKI together may conceal unique pathophysiologic processes specific to certain AKI populations, and discovering these AKI subphenotypes might help to develop targeted therapies tackling unique pathophysiological processes. In this review, we discuss the concept of AKI subphenotypes, current knowledge regarding both clinical and biomarker-driven subphenotypes, interplay with AKI subphenotypes and other ICU syndromes, and potential future and clinical implications.

Pathophysiology of Acute Kidney Injury in Malaria and Non-Malarial Febrile Illness: A Prospective Cohort Study

Acute kidney injury (AKI) is a life-threatening complication. Malaria and sepsis are leading causes of AKI in low-and-middle-income countries, but its etiology and pathogenesis are poorly understood. A prospective observational cohort study was conducted to evaluate pathways of immune and endothelial activation in children hospitalized with an acute febrile illness in Uganda. The relationship between clinical outcome and AKI, defined using the Kidney Disease: Improving Global Outcomes criteria, was investigated. The study included 967 participants (mean age 1.67 years, 44.7% female) with 687 (71.0%) positive for malaria by rapid diagnostic test and 280 (29.1%) children had a non-malarial febrile illness (NMFI). The frequency of AKI was higher in children with NMFI compared to malaria (AKI, 55.0% vs. 46.7%, p = 0.02). However, the frequency of severe AKI (stage 2 or 3 AKI) was comparable (12.1% vs. 10.5%, p = 0.45). Circulating markers of both immune and endothelial activation were associated with severe AKI. Children who had malaria and AKI had increased mortality (no AKI, 0.8% vs. AKI, 4.1%, p = 0.005), while there was no difference in mortality among children with NMFI (no AKI, 4.0% vs. AKI, 4.6%, p = 0.81). AKI is a common complication in children hospitalized with acute infections. Immune and endothelial activation appear to play central roles in the pathogenesis of AKI.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury

BACKGROUND

The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure.

METHODS

To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later.

RESULTS

Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression.

CONCLUSIONS

A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

Acute kidney injury in the critically ill: an updated review on pathophysiology and management

Acute kidney injury (AKI) is now recognized as a heterogeneous syndrome that not only affects acute morbidity and mortality, but also a patient’s long-term prognosis. In this narrative review, an update on various aspects of AKI in critically ill patients will be provided. Focus will be on prediction and early detection of AKI (e.g., the role of biomarkers to identify high-risk patients and the use of machine learning to predict AKI), aspects of pathophysiology and progress in the recognition of different phenotypes of AKI, as well as an update on nephrotoxicity and organ cross-talk. In addition, prevention of AKI (focusing on fluid management, kidney perfusion pressure, and the choice of vasopressor) and supportive treatment of AKI is discussed. Finally, post-AKI risk of long-term sequelae including incident or progression of chronic kidney disease, cardiovascular events and mortality, will be addressed.

Prognostic Biomarkers for Thrombotic Microangiopathy after Acute Graft-versus-Host Disease: A Nested Case-Control Study

Transplantation-associated thrombotic microangiopathy (TA-TMA) is a complication of allogeneic hematopoietic cell transplantation (HCT) that often occurs following the development of acute graft-versus-host disease (aGVHD). In this study, we aimed to identify early TMA biomarkers among patients with aGVHD. We performed a nested-case-control study from a prospective cohort of allogeneic HCT recipients, matching on the timing and severity of antecedent aGVHD. We identified 13 TMA cases and 25 non-TMA controls from 208 patients in the cohort. Using multivariable conditional logistic regression, the odds ratio for TMA compared with non-TMA was 2.65 (95% confidence interval [CI], 1.00 to 7.04) for every 100 ng/mL increase in terminal complement complex sC5b9 and 2.62 (95% CI, 1.56 to 4.38) for every 1000 pg/mL increase in angiopoietin-2 (ANG2) at the onset of aGVHD. ADAMTS13 and von Willebrand factor (VWF) antigens were not appreciably associated with TMA. Using a Cox regression model incorporating sC5b9 >300 ng/mL and ANG2 >3000 pg/mL at the onset of aGVHD, the adjusted hazard ratio for mortality was 5.33 (95% CI, 1.57 to 18.03) for the high-risk group (both elevated) and 4.40 (95% CI, 1.60 to 12.07) for the intermediate-risk group (one elevated) compared with the low-risk group (neither elevated). In conclusion, we found that elevated sC5b9 and ANG2 levels at the onset of aGVHD were associated with the development of TMA and possibly mortality after accounting for the timing and severity of aGVHD. The results suggest important roles of complement activation and endothelial dysfunction in the pathogenesis of TMA. Measurement of these biomarkers at the onset of aGVHD may inform prognostic enrichment for preventive trials and improve clinical care.

Identification of acute kidney injury subphenotypes

PURPOSE OF REVIEW

AKI is a complex clinical syndrome with many causes and there is a broad range of clinical presentations that vary according to duration, severity and context. Established consensus definitions of AKI are nonspecific and limited to kidney function. This reduces treatment options to generic approaches rather than individualized, cause-based strategies that have limited both understanding and management of AKI.

RECENT FINDINGS

The context and the temporal phase of kidney injury are critical features in the course of AKI and critical to timing-relevant intervention. These features are missing in generic definitions and terms used to describe AKI. Subphenotypes of AKI can be identified from novel damage biomarkers, from functional changes including creatinine trajectories, from the duration of change and from associated clinical characteristics and comorbidities. Subphenotype parameters can be combined in risk scores, or by association strategies ranging from a simple function-damage matrix to complex methods, such as machine learning. Examples of such strategies are reviewed along with tentative proposals for a revised nomenclature to facilitate description of AKI subphenotypes.

SUMMARY

Appropriate intervention requires refinement of the nomenclature of AKI to identify subphenotypes that facilitate correctly timed and selectively targeted intervention.