Toxic Nephropathies of the Tubulointerstitium: Core Curriculum 2024.

Toxic nephropathies are a clinically common group of disorders characterized by toxin-induced renal injury that can affect the glomerulus, vasculature, or tubulointerstitium. Various endogenous (eg, myoglobin, hemoglobin, monoclonal light chains, and lysozymes) and exogenous toxins (eg, therapeutic drugs, herbal medications, heavy metals, radiocontrast, intoxicants, and environmental exposures) have been implicated. The kidney's primary role of metabolism and excretion of substances via glomerular filtration and tubular secretion increases its susceptibility to their adverse effects. The structure, dose, metabolic handling, and excretory pathway of the drug/toxin through the kidney determines its nephrotoxic risk. Patient characteristics that impact risk include genetic determinants of drug metabolism, transport and excretion, immune response genes, and comorbid conditions. Clinical manifestations depend on site and severity of renal injury. Toxin-induced tubulointerstitial injury often presents as a decline in renal function and/or solute transport defects and renal solute wasting. Injury is often reversible with limited toxin exposure; however, irreversible renal injury can occur with prolonged exposure. In this Core Curriculum, we will focus on discussing mechanisms of common toxin-induced tubulointerstitial renal injury and review their causes, clinical presentations, diagnosis, and management.

Urinary Biomarkers and Kidney Injury in VA NEPHRON-D: Phenotyping Acute Kidney Injury in Clinical Trials.

RATIONALE & OBJECTIVE: Urinary biomarkers of injury, inflammation, and repair may help phenotype acute kidney injury (AKI) observed in clinical trials. We evaluated the differences in biomarkers between participants randomized to monotherapy or to combination renin-angiotensin-aldosterone system (RAAS) blockade in VA NEPHRON-D, where an increased proportion of observed AKI was acknowledged in the combination arm. STUDY DESIGN: Longitudinal analysis. SETTING & PARTICIPANTS: A substudy of the VA NEPHRON-D trial. PREDICTOR: Primary exposure was the treatment arm (combination [RAAS inhibitor] vs monotherapy). AKI is used as a stratifying variable. OUTCOME: Urinary biomarkers, including albumin, EGF (epidermal growth factor), MCP-1 (monocyte chemoattractant protein-1), YKL-40 (chitinase 3-like protein 1), and KIM-1 (kidney injury molecule-1). ANALYTICAL APPROACH: Biomarkers measured at baseline and at 12 months in trial participants were compared between treatment groups and by AKI. AKI events occurring during hospitalization were predefined safety end points in the original trial. The results were included in a meta-analysis with other large chronic kidney disease trials to assess global trends in biomarker changes. RESULTS: In 707 participants followed for a median of 2.2 years, AKI incidence was higher in the combination (20.7%) versus the monotherapy group (12.7%; relative risk [RR], 1.64 [95% CI, 1.16-2.30]). Compared with the monotherapy arm, in the combination arm the urine biomarkers at 12 months were either unchanged (MCP-1: RR, -3% [95% CI, -13% to 9%], Padj=0.8; KIM-1: RR, -10% [95% CI, -20% to 1%], Padj=0.2; EGF, RR-7% [95% CI, -12% to-1%], Padj=0.08) or lower (albuminuria: RR, -24% [95% CI, -37% to-8%], Padj=0.02; YKL: RR, -40% to-44% [95% CI, -58% to-25%], Padj<0.001). Pooled meta-analysis demonstrated reduced albuminuria in the intervention arm across 3 trials and similar trajectories in other biomarkers. LIMITATIONS: Biomarker measurement was limited to 2 time points independent of AKI events. CONCLUSIONS: Despite the increased risk of serum creatinine-defined AKI, combination RAAS inhibitor therapy was associated with unchanged or decreased urinary biomarkers at 12 months. This suggests a possible role for kidney biomarkers to further characterize kidney injury in clinical trials. PLAIN-LANGUAGE SUMMARY: The VA NEPHRON-D trial investigated inhibition of the renin-angiotensin-aldosterone system (RAAS) hormonal axis on kidney outcomes in a large population of diabetic chronic kidney disease patients. The trial was stopped early due to increased events of serum creatinine-defined acute kidney injury in the combination therapy arm. Urine biomarkers can serve as an adjunct to serum creatinine in identifying kidney injury. We found that urinary biomarkers in the combination therapy group were not associated with a pattern of harm and damage to the kidney, despite the increased number of kidney injury events in that group. This suggests that serum creatinine alone may be insufficient for defining kidney injury and supports further exploration of how other biomarkers might improve identification of kidney injury in clinical trials.

Urinary Plasminogen as a Marker of Disease Progression in Human Glomerular Disease.

RATIONALE & OBJECTIVE: Glomerular disorders have a highly variable clinical course, and biomarkers that reflect the molecular mechanisms underlying their progression are needed. Based on our previous work identifying plasminogen as a direct cause of podocyte injury, we designed this study to test the association between urine plasmin(ogen) (ie, plasmin and its precursor plasminogen) and end-stage kidney disease (ESKD). STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 1,010 patients enrolled in the CureGN Cohort with biopsy-proven glomerular disease (focal segmental glomerulosclerosis, membranous nephropathy, and immunoglobulin A nephropathy). PREDICTORS: The main predictor was urine plasmin(ogen) at baseline. Levels were measured by an electrochemiluminescent immunoassay developed de novo. Traditional clinical and analytical characteristics were used for adjustment. The ratio of urine plasmin(ogen)/expected plasmin(ogen) was evaluated as a predictor in a separate model. OUTCOME: Progression to ESKD. ANALYTICAL APPROACH: Cox regression was used to examine the association between urinary plasmin(ogen) and time to ESKD. Urinary markers were log2 transformed to approximate normal distribution and normalized to urinary creatinine (Log2uPlasminogen/cr, Log2 urinary protein/cr [UPCR]). Expected plasmin(ogen) was calculated by multiple linear regression. RESULTS: Adjusted Log2uPlasminogen/cr was significantly associated with ESKD (HR per doubling Log2 uPlasminogen/cr 1.31 [95% CI, 1.22-1.40], P<0.001). Comparison of the predictive performance of the models including Log2 uPlasminogen/cr, Log2 UPCR, or both markers showed the plasmin(ogen) model superiority. The ratio of measured/expected urine plasmin(ogen) was independently associated with ESKD: HR, 0.41 (95% CI, 0.22-0.77) if ratio<0.8 and HR 2.42 (95% CI, 1.54-3.78) if ratio>1.1 (compared with ratio between 0.8 and 1.1). LIMITATIONS: Single plasmin(ogen) determination does not allow for the study of changes over time. The use of a cohort of mostly white patients and the restriction to patients with 3 glomerular disorders limits the external validity of our analysis. CONCLUSIONS: Urinary plasmin(ogen) and the ratio of measured/expected plasmin(ogen) are independently associated with ESKD in a cohort of patients with glomerular disease. Taken together with our previous experimental findings, urinary plasmin(ogen) could be a useful biomarker in prognostic decision making and a target for the development of novel therapies in patients with proteinuria and glomerular disease. PLAIN-LANGUAGE SUMMARY: Glomerular diseases are an important cause of morbidity and mortality in patients of all ages. Knowing the individual risk of progression to dialysis or transplantation would help to plan the follow-up and treatment of these patients. Our work studies the usefulness of urinary plasminogen as a marker of progression in this context, since previous studies indicate that plasminogen may be involved in the mechanisms responsible for the progression of these disorders. Our work in a sample of 1,010 patients with glomerular disease demonstrates that urinary plasminogen (as well as the ratio of measured to expected plasminogen) is associated with the risk of progression to end-stage kidney disease. Urine plasminogen exhibited good performance and, if further validated, could enable risk stratification for timely interventions in patients with proteinuria and glomerular disease.

The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events.

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients.

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

Immune checkpoint inhibitors and kidney disease.

PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICIs) have changed the landscape of cancer treatment. However, use of ICIs can be limited by inflammatory toxicities referred to as immune-related adverse events (irAEs). ICI-associated acute kidney injury (ICI-associated AKI) affects 3-5% of ICI users. RECENT FINDINGS: With the rapidly growing indication of ICI, knowledge of ICI-associated kidney toxicity has also expanded from case series to large multicentre cohort studies. In this review, we discuss the clinical features, risk factors, clinicopathological correlations and prognosis of ICI-associated AKI from the most recent rigorously conducted retrospective cohort studies. We also discuss recent advances in diagnostic biomarker investigation, treatment and the unique challenge faced in the kidney transplant population. SUMMARY: With more comprehensive understanding of the clinical features and risk factors, ICI-associated AKI is commonly diagnosed clinically, especially given the inherent challenges performing a kidney biopsy in the cancer population; however, this highlights the urgent need for improved noninvasive diagnostic biomarkers to aid diagnosis and prognosis. Prospective studies are needed to better define the optimal treatment of ICI-associated AKI and to minimize the risk of graft loss in patients with kidney transplant who require ICIs.

Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is common in patients with coronavirus disease 2019 (COVID-19) and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers and adverse kidney outcomes among patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. EXPOSURE: 19 urinary biomarkers of injury, inflammation, and repair. OUTCOME: Composite of KDIGO (Kidney Disease: Improving Global Outcomes) stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. ANALYTICAL APPROACH: Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. RESULTS: Out of 153 patients, 24 (15.7%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR, 1.34 [95% CI, 1.14-1.57]), monocyte chemoattractant protein (MCP-1) (HR, 1.42 [95% CI, 1.09-1.84]), and kidney injury molecule 1 (KIM-1) (HR, 2.03 [95% CI, 1.38-2.99]) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR, 0.61 [95% CI, 0.47-0.79]). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. LIMITATIONS: Small sample size with low number of composite outcome events. CONCLUSIONS: Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery.

Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data.

BACKGROUND: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. METHODS: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. RESULTS: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. CONCLUSIONS: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.

Results from the TRIBE-AKI Study found associations between post-operative blood biomarkers and risk of chronic kidney disease after cardiac surgery.

Patients undergoing cardiac surgery are placed under intense physiologic stress. Blood and urine biomarkers measured peri-operatively may help identify patients at higher risk for adverse long-term kidney outcomes.We sought to determine independent associations of various biomarkers with development or progression of chronic kidney disease (CKD) following cardiac surgery. In this sub-study of the prospective cohort -TRIBE-AKI Study, we evaluated 613 adult patients undergoing cardiac surgery in Canada in our primary analysis and tested the association of 40 blood and urinary biomarkers with the primary composite outcome of CKD incidence or progression. In those with baseline estimated glomerular filtration rate (eGFR) over 60 mL/min/1.73m2, we defined CKD incidence as a 25% reduction in eGFR and an eGFR under 60. In those with baseline eGFR under 60 mL/min/1.73m2, we defined CKD progression as a 50% reduction in eGFR or eGFR under 15. Results were evaluated in a replication cohort of 310 patients from one study site in the United States. Over a median follow-up of 5.6 years, 172 patients developed the primary outcome. Each log increase in basic fibroblast growth factor (adjusted hazard ratio 1.52 [95% confidence interval 1.19, 1.93]), Kidney Injury Molecule-1 (1.51 [0.98, 2.32]), N-terminal pro-B-type natriuretic peptide (1.19 [1.01, 1.41]), and tumor necrosis factor receptor 1 (1.75 [1.18, 2.59]) were associated with outcome after adjustment for demographic factors, serum creatinine, and albuminuria. Similar results were noted in the replication cohort. Although there was no interaction by acute kidney injury in continuous analysis, mortality was higher in the no acute kidney injury group by biomarker tertile. Thus, elevated post-operative levels of blood biomarkers following cardiac surgery were independently associated with the development of CKD. These biomarkers can provide additional value in evaluating CKD incidence and progression after cardiac surgery.

Rationale and design of the Kidney Precision Medicine Project.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

The Association of COVID-19 With Acute Kidney Injury Independent of Severity of Illness: A Multicenter Cohort Study.

RATIONALE & OBJECTIVE: Although coronavirus disease 2019 (COVID-19) has been associated with acute kidney injury (AKI), it is unclear whether this association is independent of traditional risk factors such as hypotension, nephrotoxin exposure, and inflammation. We tested the independent association of COVID-19 with AKI. STUDY DESIGN: Multicenter, observational, cohort study. SETTING & PARTICIPANTS: Patients admitted to 1 of 6 hospitals within the Yale New Haven Health System between March 10, 2020, and August 31, 2020, with results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing via polymerase chain reaction of a nasopharyngeal sample. EXPOSURE: Positive test for SARS-CoV-2. OUTCOME: AKI by KDIGO (Kidney Disease: Improving Global Outcomes) criteria. ANALYTICAL APPROACH: Evaluated the association of COVID-19 with AKI after controlling for time-invariant factors at admission (eg, demographic characteristics, comorbidities) and time-varying factors updated continuously during hospitalization (eg, vital signs, medications, laboratory results, respiratory failure) using time-updated Cox proportional hazard models. RESULTS: Of the 22,122 patients hospitalized, 2,600 tested positive and 19,522 tested negative for SARS-CoV-2. Compared with patients who tested negative, patients with COVID-19 had more AKI (30.6% vs 18.2%; absolute risk difference, 12.5% [95% CI, 10.6%-14.3%]) and dialysis-requiring AKI (8.5% vs 3.6%) and lower rates of recovery from AKI (58% vs 69.8%). Compared with patients without COVID-19, patients with COVID-19 had higher inflammatory marker levels (C-reactive protein, ferritin) and greater use of vasopressors and diuretic agents. Compared with patients without COVID-19, patients with COVID-19 had a higher rate of AKI in univariable analysis (hazard ratio, 1.84 [95% CI, 1.73-1.95]). In a fully adjusted model controlling for demographic variables, comorbidities, vital signs, medications, and laboratory results, COVID-19 remained associated with a high rate of AKI (adjusted hazard ratio, 1.40 [95% CI, 1.29-1.53]). LIMITATIONS: Possibility of residual confounding. CONCLUSIONS: COVID-19 is associated with high rates of AKI not fully explained by adjustment for known risk factors. This suggests the presence of mechanisms of AKI not accounted for in this analysis, which may include a direct effect of COVID-19 on the kidney or other unmeasured mediators. Future studies should evaluate the possible unique pathways by which COVID-19 may cause AKI.

Urine interleukin-9 and tumor necrosis factor-α for prognosis of human acute interstitial nephritis.

BACKGROUND: We previously demonstrated that urine interleukin (IL)-9 and tumor necrosis factor (TNF)-α can distinguish acute interstitial nephritis (AIN) from other causes of acute kidney injury. Here we evaluated the role of these biomarkers to prognosticate kidney function in patients with AIN. METHODS: In a cohort of participants with biopsy-proven, adjudicated AIN, we tested the association of histological features and urine biomarkers (IL-9 and TNF-α) with estimated glomerular filtration rate measured 6 months after diagnosis (6 m-eGFR) controlling for eGFR before AIN and albuminuria. We also evaluated subgroups in whom corticosteroid use was associated with 6 m-eGFR. RESULTS: In the 51 (93%) of the 55 participants with complete data, median (interquartile range) eGFR before and 6 m after AIN were 41 (27-69) and 28 (13-47) mL/min/1.73 m2, respectively. Patients with higher severity of interstitial fibrosis had lower 6 m-eGFR, whereas those with higher tubulointerstitial infiltrate had higher 6 m-eGFR. IL-9 levels were associated with lower 6 m-eGFR only in the subset of patients who did not receive corticosteroids [6m-eGFR per doubling of IL-9, -6.0 (-9.4 to -2.6) mL/min/1.73 m2]. Corticosteroid use was associated with higher 6 m-eGFR [20.9 (0.2, 41.6) mL/min/1.73 m2] only in those with urine IL-9 above the median (>0.66 ng/g) but not in others. CONCLUSIONS: Urine IL-9 was associated with lower 6 m-eGFR only in participants not treated with corticosteroids. Corticosteroid use was associated with higher 6 m-eGFR in those with high urine IL-9. These findings provide a framework for IL-9-guided clinical trials to test efficacy of immunosuppressive therapy in patients with AIN.

A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children.

BACKGROUND: Timely prediction of AKI in children can allow for targeted interventions, but the wealth of data in the electronic health record poses unique modeling challenges. METHODS: We retrospectively reviewed the electronic medical records of all children younger than 18 years old who had at least two creatinine values measured during a hospital admission from January 2014 through January 2018. We divided the study population into derivation, and internal and external validation cohorts, and used five feature selection techniques to select 10 of 720 potentially predictive variables from the electronic health records. Model performance was assessed by the area under the receiver operating characteristic curve in the validation cohorts. The primary outcome was development of AKI (per the Kidney Disease Improving Global Outcomes creatinine definition) within a moving 48-hour window. Secondary outcomes included severe AKI (stage 2 or 3), inpatient mortality, and length of stay. RESULTS: Among 8473 encounters studied, AKI occurred in 516 (10.2%), 207 (9%), and 27 (2.5%) encounters in the derivation, and internal and external validation cohorts, respectively. The highest-performing model used a machine learning-based genetic algorithm, with an overall receiver operating characteristic curve in the internal validation cohort of 0.76 [95% confidence interval (CI), 0.72 to 0.79] for AKI, 0.79 (95% CI, 0.74 to 0.83) for severe AKI, and 0.81 (95% CI, 0.77 to 0.86) for neonatal AKI. To translate this prediction model into a clinical risk-stratification tool, we identified high- and low-risk threshold points. CONCLUSIONS: Using various machine learning algorithms, we identified and validated a time-updated prediction model of ten readily available electronic health record variables to accurately predict imminent AKI in hospitalized children.

Association of plasma-soluble ST2 and galectin-3 with cardiovascular events and mortality following cardiac surgery.

BACKGROUND: Cardiac surgery induces hemodynamic stress on the myocardium, and this process can be associated with significant post-operative morbidity and mortality. Soluble suppression of tumorigenicity 2 (sST2) and galectin-3 (gal-3) are biomarkers of myocardial remodeling and fibrosis; however, their potential association with post-operative changes is unknown. METHODS: We measured peri-operative plasma sST2 and gal-3 levels in two prospective cohorts (TRIBE-AKI and NNE) of over 1800 patients who underwent cardiac surgery. sST2 and gal-3 levels were evaluated for association with a composite primary outcome of cardiovascular event or mortality over median follow-up periods of 3.4 and 6.0 years, respectively, for the two cohorts. Meta-analysis of hazard ratio estimates from the cohorts was performed using random effects models. RESULTS: Cohorts demonstrated event rates of 70.2 and 66.8 per 1000 person-years for the primary composite outcome. After adjustment for clinical covariates, higher post-operative sST2 and gal-3 levels were significantly associated with cardiovascular event or mortality [pooled estimate HRs: sST2 1.29 (95% CI 1.16, 1.44); gal-3 1.26 (95% CI 1.09, 1.46)]. These associations were not significantly modified by pre-operative congestive heart failure or AKI. CONCLUSIONS: Higher post-operative sST2 and gal-3 values were associated with increased incidence of cardiovascular event or mortality. These two biomarkers should be further studied for potential clinical utility for patients undergoing cardiac surgery.

Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is diagnosed based on changes in serum creatinine concentration, a late marker of this syndrome. Algorithms that predict elevated risk for AKI are of great interest, but no studies have incorporated such an algorithm into the electronic health record to assist with clinical care. We describe the experience of implementing such an algorithm. STUDY DESIGN: Prospective observational cohort study. SETTING & PARTICIPANTS: 2,856 hospitalized adults in a single urban tertiary-care hospital with an algorithm-predicted risk for AKI in the next 24 hours>15%. Alerts were also used to target a convenience sample of 100 patients for measurement of 16 urine and 6 blood biomarkers. EXPOSURE: Clinical characteristics at the time of pre-AKI alert. OUTCOME: AKI within 24 hours of pre-AKI alert (AKI24). ANALYTICAL APPROACH: Descriptive statistics and univariable associations. RESULTS: At enrollment, mean predicted probability of AKI24 was 19.1%; 18.9% of patients went on to develop AKI24. Outcomes were generally poor among this population, with 29% inpatient mortality among those who developed AKI24 and 14% among those who did not (P<0.001). Systolic blood pressure<100mm Hg (28% of patients with AKI24 vs 18% without), heart rate>100 beats/min (32% of patients with AKI24 vs 24% without), and oxygen saturation<92% (15% of patients with AKI24 vs 6% without) were all more common among those who developed AKI24. Of all biomarkers measured, only hyaline casts on urine microscopy (72% of patients with AKI24 vs 25% without) and fractional excretion of urea nitrogen (20% [IQR, 12%-36%] among patients with AKI24 vs 34% [IQR, 25%-44%] without) differed between those who did and did not develop AKI24. LIMITATIONS: Single-center study, reliance on serum creatinine level for AKI diagnosis, small number of patients undergoing biomarker evaluation. CONCLUSIONS: A real-time AKI risk model was successfully integrated into the EHR.

The Association of Angiogenesis Markers With Acute Kidney Injury and Mortality After Cardiac Surgery.

RATIONALE & OBJECTIVE: The process of angiogenesis after kidney injury may determine recovery and long-term outcomes. We evaluated the association of angiogenesis markers with acute kidney injury (AKI) and mortality after cardiac surgery. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: 1,444 adults undergoing cardiac surgery in the TRIBE-AKI (Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury) cohort. EXPOSURES: Plasma concentrations of 2 proangiogenic markers (vascular endothelial growth factor A [VEGF] and placental growth factor [PGF]) and 1 antiangiogenic marker (soluble VEGF receptor 1 [VEGFR1]), measured pre- and postoperatively within 6 hours after surgery. OUTCOMES: AKI, long AKI duration (≥7 days), and 1-year all-cause mortality. ANALYTICAL APPROACH: Multivariable logistic regression. RESULTS: Following cardiac surgery, plasma VEGF concentrations decreased 2-fold, and PGF and VEGFR1 concentrations increased 1.5- and 8-fold, respectively. There were no meaningful associations of preoperative concentrations of angiogenic markers with outcomes of AKI and mortality. Higher postoperative VEGF and PGF concentrations were independently associated with lower odds of AKI (adjusted ORs of 0.89 [95% CI, 0.82-0.98] and 0.69 [95% CI, 0.55-0.87], respectively), long AKI duration (0.65 [95% CI, 0.49-0.87] and 0.48 [95% CI, 0.28-0.82], respectively), and mortality (0.74 [95% CI, 0.62-0.89] and 0.46 [95% CI, 0.31-0.68], respectively). In contrast, higher postoperative VEGFR1 concentrations were independently associated with higher odds of AKI (1.56; 95% CI, 1.31-1.87), long AKI duration (1.75; 95% CI, 1.09-2.82), and mortality (2.28; 95% CI, 1.61-3.22). LIMITATIONS: Angiogenesis markers were not measured after hospital discharge, so we were unable to determine long-term trajectories of angiogenesis marker levels during recovery and follow-up. CONCLUSIONS: Higher levels of postoperative proangiogenic markers, VEGF and PGF, were associated with lower AKI and mortality risk, whereas higher postoperative antiangiogenic VEGFR1 levels were associated with higher risk for AKI and mortality.

Plasma Biomarkers and Kidney Function Decline in Early and Established Diabetic Kidney Disease.

Biomarkers of diverse pathophysiologic mechanisms may improve risk stratification for incident or progressive diabetic kidney disease (DKD) in persons with type 2 diabetes. To evaluate such biomarkers, we performed a nested case-control study (n=190 cases of incident DKD and 190 matched controls) and a prospective cohort study (n=1156) using banked baseline plasma samples from participants of randomized, controlled trials of early (ACCORD) and advanced (VA NEPHRON-D) DKD. We assessed the association and discrimination obtained with baseline levels of plasma TNF receptor-1 (TNFR-1), TNFR-2, and kidney injury molecule-1 (KIM-1) for the outcomes of incident DKD (ACCORD) and progressive DKD (VA-NEPHRON-D). At baseline, median concentrations of TNFR-1, TNFR-2, and KIM-1 were roughly two-fold higher in the advanced DKD population (NEPHRON-D) than in the early DKD population (ACCORD). In both cohorts, patients who reached the renal outcome had higher baseline levels than those who did not reach the outcome. Associations between doubling in TNFR-1, TNFR-2, and KIM-1 levels and risk of the renal outcomes were significant for both cohorts. Inclusion of these biomarkers in clinical models increased the area under the curve (SEM) for predicting the renal outcome from 0.68 (0.02) to 0.75 (0.02) in NEPHRON-D. Systematic review of the literature illustrated high consistency in the association between these biomarkers of inflammation and renal outcomes in DKD. In conclusion, TNFR-1, TNFR-2, and KIM-1 independently associated with higher risk of eGFR decline in persons with early or advanced DKD. Moreover, addition of these biomarkers to clinical prognostic models significantly improved discrimination for the renal outcome.

Performance of Serum Creatinine and Kidney Injury Biomarkers for Diagnosing Histologic Acute Tubular Injury.

BACKGROUND: The diagnosis of acute kidney injury (AKI), which is currently defined as an increase in serum creatinine (Scr) concentration, provides little information on the condition's actual cause. To improve phenotyping of AKI, many urinary biomarkers of tubular injury are being investigated. Because AKI cases are not frequently biopsied, the diagnostic accuracy of concentrations of Scr and urinary biomarkers for histologic acute tubular injury is unknown. STUDY DESIGN: Cross-sectional analysis from multicenter prospective cohort. SETTINGS & PARTICIPANTS: Hospitalized deceased kidney donors on whom kidney biopsies were performed at the time of organ procurement for histologic evaluation. PREDICTORS: (1) AKI diagnosed by change in Scr concentration during donor hospitalization and (2) concentrations of urinary biomarkers (neutrophil gelatinase-associated lipocalin [NGAL], liver-type fatty acid-binding protein [L-FABP], interleukin 18 [IL-18], and kidney injury molecule 1 [KIM-1]) measured at organ procurement. OUTCOME: Histologic acute tubular injury. RESULTS: Of 581 donors, 98 (17%) had mild acute tubular injury and 57 (10%) had severe acute tubular injury. Overall, Scr-based AKI had poor diagnostic performance for identifying histologic acute tubular injury and 49% of donors with severe acute tubular injury did not have AKI. The area under the receiver operating characteristic curve (AUROC) of change in Scr concentration for diagnosing severe acute tubular injury was 0.58 (95% CI, 0.49-0.67) and for any acute tubular injury was 0.52 (95% CI, 0.45-0.58). Compared with Scr concentration, NGAL concentration demonstrated higher AUROC for diagnosing both severe acute tubular injury (0.67; 95% CI, 0.60-0.74; P=0.03) and any acute tubular injury (0.60; 95% CI, 0.55-0.66; P=0.005). In donors who did not have Scr-based AKI, NGAL concentrations were higher with increasing severities of acute tubular injury (subclinical AKI). However, compared with Scr concentration, AUROCs for acute tubular injury diagnosis were not significantly higher for urinary L-FABP, IL-18, or KIM-1. LIMITATIONS: The spectrum of AKI cause in deceased donors may be different from that of a general hospitalized population. CONCLUSIONS: Concentrations of Scr and kidney injury biomarkers (L-FABP, IL-18, and KIM-1) lack accuracy for diagnosing acute tubular injury in hospitalized deceased donors. Although urinary NGAL concentration had slightly higher discrimination for acute tubular injury than did Scr concentration, its overall AUROC was still modest.

Application of new acute kidney injury biomarkers in human randomized controlled trials.

The use of novel biomarkers of acute kidney injury (AKI) in clinical trials may help evaluate treatments for AKI. Here we explore potential applications of biomarkers in simulated clinical trials of AKI using data from the TRIBE-AKI multicenter, prospective cohort study of patients undergoing cardiac surgery. First, in a hypothetical trial of an effective therapy at the time of acute tubular necrosis to prevent kidney injury progression, use of an indirect kidney injury marker such as creatinine compared to a new direct biomarker of kidney injury reduces the proportion of true acute tubular necrosis cases enrolled. The result is a lower observed relative risk reduction with the therapy, and lower statistical power to detect a therapy effect at a given sample size. Second, the addition of AKI biomarkers (interleukin-18 and NGAL) to clinical risk factors as eligibility criteria for trial enrollment in early AKI has the potential to increase the proportion of patients who will experience AKI progression and reduce trial cost. Third, we examine AKI biomarkers as outcome measures for the purposes of identifying therapies that warrant further testing in larger, multicenter, multi-country trials. In the hypothetical trial of lower cardiopulmonary bypass time to reduce the risk of postoperative AKI, the sample size required to detect a reduction in AKI is lower if new biomarkers are used to define AKI rather than serum creatinine. Thus, incorporation of new biomarkers of AKI has the potential to increase statistical power, decrease the sample size, and lower the cost of AKI trials.