KEY POINTS: Health utility profiles can be identified at 60 days after AKI. Patient subgroups with distinct health utility profiles have different characteristics at index hospitalization and outcomes at 1 year. These profiles may be useful when considering resources to improve the physical and emotional health of patients after AKI. BACKGROUND: A large amount of interindividual variability exists in health-related quality of life outcomes after AKI. This study aimed to determine whether subgroups of early AKI survivors could be identified on the basis of distinct health utility impairment profiles ascertained at 60 days after AKI and whether these subgroups differed in clinical and biomarker characteristics at index hospitalization and outcomes at 1-year follow-up. METHODS: This retrospective analysis used data from the Biologic Markers of Renal Recovery for the Kidney study, an observational subcohort of the Acute Renal Failure Trial Network study. Of 402 patients who survived to 60 days after AKI, 338 completed the Health Utility Index 3 survey, which measures impairments in eight health attributes. Latent class analysis was used to identify subgroups of patients with distinct health utility profiles. RESULTS: Three subgroups with distinct health utility impairment profiles were identified: Low (28% of participants), Moderate (58%), and High (14%) with a median of one, four, and six impairments across the eight health attributes at 60 days after AKI, respectively. Patient subgroups differed in weight, history of cerebrovascular disease, intensity of dialysis, hospital length of stay, and dialysis dependence. Serum creatinine and blood urea nitrogen at index hospitalization did not differ among the three subgroups. The High impairment subgroup had higher levels of IL-6 and soluble TNF receptor 2 at study day 1. The three subgroups had different 1-year mortality rates: 5% in the Low, 21% in the Moderate, and 52% in the High impairment subgroup. CONCLUSION: Patient subgroups with distinct health utility impairment profiles can be identified 60 days after AKI. These subgroups have different characteristics at index hospitalization. A higher level of impairment at 60 days was associated with decreased survival.

Background

Acute kidney injury (AKI) is independently associated with increased morbidity and mortality. Quality improvement has been identified as an important goal in the care of patients with AKI. Different settings can be targeted to improve AKI care, broadly classified these include the inpatient and outpatient environments. In this paper, we will emphasize quality indicators associated with the management and secondary prevention of AKI in hospitalized patients to limit the severity, duration, and complications.

Methods

During the 22nd Acute Disease Quality Initiative (ADQI) consensus conference, a multidisciplinary group of experts discussed the evidence and used a modified Delphi process to achieve consensus on recommendations for AKI-related quality indicators (QIs) and care processes to improve patient outcomes. The management and secondary prevention of AKI in hospitalized patients were discussed, and recommendations were summarized.

Results

The first step in optimizing the quality of AKI management is the determination of baseline performance. Data regarding each institution's/center's performance can provide a reference point from which to benchmark quality efforts. Quality program initiatives should prioritize achievable goals likely to have the highest impact according to the setting and context. Key AKI quality metrics should include improvement in timely recognition, appropriate diagnostic workup, and implementation of known interventions that limit progression and severity, facilitating recovery, and mitigating AKI-associated complications. We propose the Recognition-Action-Results framework to plan, measure, and report the progress toward improving AKI management quality.

Conclusions

These recommendations identified and outlined an approach to define and evaluate the quality of AKI management in hospitalized patients.

Rationale & objective

Uric acid is excreted by the kidney and accumulates in acute kidney injury (AKI). Whether higher plasma uric acid level predisposes to AKI or its complications is not known.

Study design

Prospective observational cohort study.

Setting & participants

2 independent cohorts of critically ill patients: (1) 208 patients without AKI admitted to the intensive care unit (ICU) at Brigham & Women's Hospital between October 2008 and December 2016; and (2) 250 participants with AKI requiring renal replacement therapy (RRT) who had not yet initiated RRT enrolled in the Acute Renal Failure Trial Network (ATN) Study.

Exposure

Plasma uric acid level upon ICU admission and before RRT initiation in the ICU and ATN Study cohorts, respectively.

Outcomes

Incident AKI and 60-day mortality in the ICU and ATN Study cohorts, respectively.

Analytical approach

Logistic regression models were used to test the association of plasma uric acid level with incident AKI and 60-day mortality.

Results

In the ICU cohort, median plasma uric acid level was 4.7 (interquartile range [IQR], 3.6-6.4) mg/dL, and 40 patients (19.2%) developed AKI. Higher plasma uric acid levels associated with incident AKI, but this association was confounded by serum creatinine level and was not significant after multivariable adjustment (adjusted OR per doubling of uric acid, 1.50; 95% CI, 0.80-2.81). In the ATN Study cohort, median plasma uric acid level was 11.1 (IQR, 8.6-14.2) mg/dL, and 125 participants (50.0%) died within 60 days. There was no statistically significant association between plasma uric acid levels and 60-day mortality in either unadjusted models or after multivariable adjustment for demographic, severity-of-illness, and kidney-specific covariates (adjusted OR per doubling of uric acid, 1.15; 95% CI, 0.71-1.86).

Limitations

Heterogeneity of ICU patients.

Conclusions

Plasma uric acid levels upon ICU admission or before RRT initiation are not independently associated with adverse clinical outcomes in critically ill patients.

Background

Among critically ill patients with acute kidney injury (AKI), earlier initiation of renal replacement therapy (RRT) may mitigate fluid accumulation and confer better outcomes among individuals with greater fluid overload at randomization.

Methods

We conducted a pre-planned post hoc analysis of the STandard versus Accelerated initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial. We evaluated the effect of accelerated RRT initiation on cumulative fluid balance over the course of 14 days following randomization using mixed models after censoring for death and ICU discharge. We assessed the modifying effect of baseline fluid balance on the impact of RRT initiation strategy on key clinical outcomes. Patients were categorized in quartiles of baseline fluid balance, and the effect of accelerated versus standard RRT initiation on clinical outcomes was assessed in each quartile using risk ratios (95% CI) for categorical variables and mean differences (95% CI) for continuous variables.

Results

Among 2927 patients in the modified intention-to-treat analysis, 2738 had available data on baseline fluid balance and 2716 (92.8%) had at least one day of fluid balance data following randomization. Over the subsequent 14 days, participants allocated to the accelerated strategy had a lower cumulative fluid balance compared to those in the standard strategy (4509 (- 728 to 11,698) versus 5646 (0 to 13,151) mL, p = 0.03). Accelerated RRT initiation did not confer greater 90-day survival in any of the baseline fluid balance quartiles (quartile 1: RR 1.11 (95% CI 0.92 to 1.34), quartile 2: RR 1.03 (0.87 to 1.21); quartile 3: RR 1.08 (95% CI 0.91 to 1.27) and quartile 4: RR 0.87 (95% CI 0.73 to 1.03), p value for trend 0.08).

Conclusions

Earlier RRT initiation in critically ill patients with AKI conferred a modest attenuation of cumulative fluid balance. Nonetheless, among patients with greater fluid accumulation at randomization, accelerated RRT initiation did not have an impact on all-cause mortality.

Trial registration

ClinicalTrials.gov number, https://clinicaltrials.gov/ct2/show/NCT02568722 , registered October 6, 2015.

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of >90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD.

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Introduction

About one-third of critically ill patients with acute kidney injury (AKI) develop persistently decreased kidney function, known as acute kidney disease (AKD), which may progress to chronic kidney disease (CKD). Although sepsis is the most common cause of AKI, little is known about sepsis-associated AKD.

Methods

Using data from a large randomized trial including 1341 patients with septic shock, we studied patients with stage 2 or 3 AKI on day 1 of hospitalization. We defined AKD as a persistently reduced glomerular filtration rate for >7 days. In addition to clinical data, we measured several urinary biomarkers (tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7 [TIMP-2∗IGFBP7], neutrophil gelatinase-associated lipocalin [NGAL], kidney injury molecule-1 [KIM-1], liver-type fatty acid binding protein, and type 4 collagen) at 0, 6, and 24 hours, to predict AKD.

Results

Of 598 patients, 119 (19.9%) died within 7 days, 318 (53.2%) had early reversal of AKI within the first 7 days, whereas 161 (26.9%) developed AKD. In patients with early reversal, 45 (14.2%) had relapsed AKI after early reversal, and only about one-third of these recovered. Among patients developing AKD, only 15 (9.3%) recovered renal function prior to discharge. Male sex, African American race, and underlying CKD were more predominant in patients developing AKD. None of the biomarkers tested performed well for prediction of AKD, although NGAL modestly increased the performance of a clinical model.

Conclusions

AKD is common in patients with septic shock, especially among African American males and those with underlying CKD. Existing AKI biomarkers have limited utility for predicting AKD but might be useful together with clinical variables. Novel predictive biomarkers for renal recovery are needed.

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.