New biomarkers in acute kidney injury.

Acute kidney injury (AKI) is a commonly encountered clinical syndrome. Although it often complicates community acquired illness, it is more common in hospitalized patients, particularly those who are critically ill or who have undergone major surgery. Approximately 20% of hospitalized adult patients develop an AKI during their hospital care, and this rises to nearly 60% in the critically ill, depending on the population being considered. In general, AKI is more common in older adults, in those with preexisting chronic kidney disease and in those with known risk factors for AKI (including diabetes and hypertension). The development of AKI is associated with an increase in both mortality and morbidity, including the development of post-AKI chronic kidney disease. Currently, AKI is defined by a rise in serum creatinine from either a known or derived baseline value and/or oliguria or anuria. However, clinicians may fail to recognize the initial development of AKI because of a delay in the rise of serum creatinine or because of inaccurate urine output monitoring. This, in turn, delays any putative measures to treat AKI or to limit its degree. Consequently, efforts have focused on new biomarkers associated with AKI that may allow early recognition of this syndrome with the intent that this will translate into improved patient outcomes. Here we outline current biomarkers associated with AKI and explore their potential in aiding diagnosis, understanding the pathophysiology and directing therapy.

The Road to Precision Medicine for Acute Kidney Injury.

OBJECTIVES: Acute kidney injury (AKI) is a common form of organ dysfunction in the ICU. AKI is associated with adverse short- and long-term outcomes, including high mortality rates, which have not measurably improved over the past decade. This review summarizes the available literature examining the evidence of the need for precision medicine in AKI in critical illness, highlights the current evidence for heterogeneity in the field of AKI, discusses the progress made in advancing precision in AKI, and provides a roadmap for studying precision-guided care in AKI. DATA SOURCES: Medical literature regarding topics relevant to precision medicine in AKI, including AKI definitions, epidemiology, and outcomes, novel AKI biomarkers, studies of electronic health records (EHRs), clinical trial design, and observational studies of kidney biopsies in patients with AKI. STUDY SELECTION: English language observational studies, randomized clinical trials, reviews, professional society recommendations, and guidelines on areas related to precision medicine in AKI. DATA EXTRACTION: Relevant study results, statements, and guidelines were qualitatively assessed and narratively synthesized. DATA SYNTHESIS: We synthesized relevant study results, professional society recommendations, and guidelines in this discussion. CONCLUSIONS: AKI is a syndrome that encompasses a wide range of underlying pathologies, and this heterogeneity has hindered the development of novel therapeutics for AKI. Wide-ranging efforts to improve precision in AKI have included the validation of novel biomarkers of AKI, leveraging EHRs for disease classification, and phenotyping of tubular secretory clearance. Ongoing efforts such as the Kidney Precision Medicine Project, identifying subphenotypes in AKI, and optimizing clinical trials and endpoints all have great promise in advancing precision medicine in AKI.

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.

Sepsis-associated acute kidney injury: recent advances in enrichment strategies, sub-phenotyping and clinical trials.

Acute kidney injury (AKI) often complicates sepsis and is associated with high morbidity and mortality. In recent years, several important clinical trials have improved our understanding of sepsis-associated AKI (SA-AKI) and impacted clinical care. Advances in sub-phenotyping of sepsis and AKI and clinical trial design offer unprecedented opportunities to fill gaps in knowledge and generate better evidence for improving the outcome of critically ill patients with SA-AKI. In this manuscript, we review the recent literature of clinical trials in sepsis with focus on studies that explore SA-AKI as a primary or secondary outcome. We discuss lessons learned and potential opportunities to improve the design of clinical trials and generate actionable evidence in future research. We specifically discuss the role of enrichment strategies to target populations that are most likely to derive benefit and the importance of patient-centered clinical trial endpoints and appropriate trial designs with the aim to provide guidance in designing future trials.

CCL14 Predicts Oliguria and Dialysis Requirement in Patients with Moderate to Severe Acute Kidney Injury.

INTRODUCTION: AKI is a frequent complication of critical illness and portends poor outcome. CCL14 is a validated predictor of persistent severe AKI in critically ill patients. We examined the association of CCL14 with urine output within 48 h. METHODS: In pooled data from 2 studies of critically ill patients with KDIGO stage 2-3 AKI, CCL14 was measured by NEPHROCLEAR™ CCL14 Test on the Astute 140® Meter (low, intermediate, and high categories [1.3 and 13 ng/mL]). Average hourly urine output over 48 h, stage 3 AKI per urine output criterion on day 2, and composite of dialysis or death within 7 days were examined using multivariable mixed and logistic regression models. RESULTS: Of the 497 subjects with median age of 65 (56-74) years, 49% (242/497) were on diuretics. CCL14 concentration was low in 219 (44%), intermediate in 217 (44%), and high in 61 (12%) patients. In mixed regression analysis, hourly urine output over time was different within each CCL14 risk category based on diuretic use due to significant three-way interaction (p < 0.001). In logistic regression analysis, CCL14 risk category was independently associated with low urine output on day 2 per KDIGO stage 3 (adjusted for diuretic use and baseline clinical variables), and composite of dialysis or death within 7 days (adjusted for urine output within 48 h of CCL14 measurement). CONCLUSIONS: CCL14 measured in patients with moderate to severe AKI is associated with urine output trajectory within 48 h, oliguria on day 2, and dialysis within 7 days.

Assessing the role of Chemokine (C-C motif) ligand 14 in AKI: a European consensus meeting.

BACKGROUND: Urinary Chemokine (C-C motif) ligand 14 (CCL14) is a biomarker associated with persistent severe acute kidney injury (AKI). There is limited data to support the implementation of this AKI biomarker to guide therapeutic actions. METHODS: Sixteen AKI experts with clinical CCL14 experience participated in a Delphi-based method to reach consensus on when and how to potentially use CCL14. Consensus was defined as ≥ 80% agreement (participants answered with 'Yes', or three to four points on a five-point Likert Scale). RESULTS: Key consensus areas for CCL14 test implementation were: identifying challenges and mitigations, developing a comprehensive protocol and pairing it with a treatment plan, and defining the target population. The majority agreed that CCL14 results can help to prioritize AKI management decisions. CCL14 levels above the high cutoff (> 13 ng/mL) significantly changed the level of concern for modifying the AKI treatment plan (p < 0.001). The highest level of concern to modify the treatment plan was for discussions on renal replacement therapy (RRT) initiation for CCL14 levels > 13 ng/mL. The level of concern for discussion on RRT initiation between High and Low, and between Medium and Low CCL14 levels, showed significant differences. CONCLUSION: Real world urinary CCL14 use appears to provide improved care options to patients at risk for persistent severe AKI. Experts believe there is a role for CCL14 in AKI management and it may potentially reduce AKI-disease burden. There is, however, an urgent need for evidence on treatment decisions and adjustments based on CCL14 results.

Predicting the Development of Renal Replacement Therapy Indications by Combining the Furosemide Stress Test and Chemokine (C-C Motif) Ligand 14 in a Cohort of Postsurgical Patients.

OBJECTIVES: Optimal timing of renal replacement therapy (RRT) initiation in severe acute kidney injury (AKI) remains controversial. Initiation of treatment early in the course of AKI may lead to some patients undergoing unnecessary RRT, whereas delayed treatment is associated with increased mortality. This study aims to investigate whether the combination of the furosemide stress test (FST) and AKI-associated biomarkers can predict the development of indications for RRT. DESIGN: Single-center, prospective, observational study. SETTING: University Hospital of Muenster, Germany. PATIENTS: Critically ill, postoperative patients with moderate AKI (Kidney Disease: Improving Global Outcomes stage 2) and risk factors for further progression (vasopressors and/or mechanical ventilation) receiving an FST. INTERVENTIONS: Sample collection and measurement of different biomarkers (chemokine [C-C motif] ligand 14 [CCL14], neutrophil gelatinase-associated lipocalin, dipeptidyl peptidase 3). MEASUREMENT AND MAIN RESULTS: The primary endpoint was the development of greater than or equal to one predefined RRT indications (hyperkalemia [≥ 6 mmol/L], diuretic-resistant hypervolemia, high urea serum levels [≥ 150 mg/dL], severe metabolic acidosis [pH ≤ 7.15], oliguria [urinary output < 200 mL/12 hr], or anuria). Two hundred eight patients were available for the primary analysis with 108 having a negative FST (urine output < 200 mL in 2 hr following FST). Ninety-eight patients (47%) met the primary endpoint, 82% in the FST negative cohort. At the time of inclusion, the combination of a negative FST test and high urinary CCL14 levels had a significantly higher predictive value for the primary endpoint with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% CI, 0.82-0.92) compared with FST or CCL14 alone (AUC, 0.79; 95% CI, 0.74-0.85 and AUC, 0.83; 95% CI, 0.77-0.89; p < 0.001, respectively). Other biomarkers showed lower AUCs. CONCLUSIONS: The combination of the FST with the renal biomarker CCL14 predicts the development of indications for RRT.

Real-World Use of AKI Biomarkers: A Quality Improvement Project Using Urinary Tissue Inhibitor Metalloprotease-2 and Insulin-Like Growth Factor Binding Protein 7 ([TIMP-2]*[IGFBP7]).

INTRODUCTION: Novel urinary biomarkers, including tissue inhibitor metalloprotease-2 and insulin-like growth factor binding protein 7 ([TIMP-2]*[IGFBP7]), have been developed to identify patients at risk for acute kidney injury (AKI). We investigated the "real-world" clinical utility of [TIMP-2]*[IGFBP7] in preventing AKI. METHODS: We performed a before and after single-center quality improvement study of intensive care unit (ICU) patients at risk for severe (KDIGO stage 2 or 3) AKI. In the prospective cohort, ICU providers were allowed to order [TIMP-2]*[IGFBP7] for patients at their discretion, then offered AKI practice recommendations based on the results. Outcomes were compared to a historical cohort in which biomarker values were not reported to clinical teams. RESULTS: There was no difference in 7-day progression to severe AKI between the prospective (n = 116) and historical cohorts (n = 63) when [TIMP-2]*[IGFBP7] ≥0.3 (24 [28%] versus 8 [21%], p = 0.38) despite more stage 1 AKI at time of biomarker measurement in the prospective cohort (58 [67%] versus 9 [23%], p < 0.001). In the prospective cohort, patients with higher [TIMP-2]*[IGFBP7] values were more likely to receive a nephrology consult. Early consultation (within 24 h of biomarker measurement, n = 20) had a nonsignificant trend toward net negative volume balance (-1,787 mL [6,716 mL] versus + 4,974 mL [15,540 mL]) and more diuretic use (19 [95%] versus 8 [80%]) and was associated with less severe AKI (9 [45%] versus 10 [100%], p = 0.004) and inpatient dialysis (2 [10%] versus 7 [70%], p = 0.002) compared to delayed consultation (n = 10). CONCLUSIONS: Despite the prospective cohort having more preexisting stage 1 AKI, there were equal rates of progression to severe AKI in the prospective and historical cohorts. In the setting of [TIMP-2]*[IGFBP7] reporting, there were more nephrology consults in response to elevated biomarker levels. Early nephrology consultation resulted in improved volume balance and favorable outcomes compared to delayed consultation.

Sepsis-associated acute kidney injury-treatment standard.

Sepsis is a host's deleterious response to infection, which could lead to life-threatening organ dysfunction. Sepsis-associated acute kidney injury (SA-AKI) is the most frequent organ dysfunction and is associated with increased morbidity and mortality. Sepsis contributes to ≈50% of all AKI in critically ill adult patients. A growing body of evidence has unveiled key aspects of the clinical risk factors, pathobiology, response to treatment and elements of renal recovery that have advanced our ability to detect, prevent and treat SA-AKI. Despite these advancements, SA-AKI remains a critical clinical condition and a major health burden, and further studies are needed to diminish the short and long-term consequences of SA-AKI. We review the current treatment standards and discuss novel developments in the pathophysiology, diagnosis, outcome prediction and management of SA-AKI.

Digital health utilities in acute kidney injury management.

PURPOSE OF REVIEW: Acute kidney injury (AKI) is a highly prevalent clinical syndrome that substantially impacts patient outcomes. It is accepted by the clinical communities that the management of AKI is time-sensitive. Unfortunately, despite growing proof of its preventability, AKI management remains suboptimal in community, acute care, and postacute care settings. Digital health solutions comprise various tools and models to improve care processes and patient outcomes in multiple medical fields. AKI development, progression, recovery, or lack thereof, offers tremendous opportunities for developing, validating, and implementing digital health solutions in multiple settings. This article will review the definitions and components of digital health, the characteristics of AKI that allow digital health solutions to be considered, and the opportunities and threats in implementing these solutions. RECENT FINDINGS: Over the past two decades, the academic output related to the use of digital health solutions in AKI has exponentially grown. While this indicates the growing interest in the topic, most topics are primarily related to clinical decision support by detecting AKI within hospitals or using artificial intelligence or machine learning technologies to predict AKI within acute care settings. However, recently, projects to assess the impact of digital health solutions in more complex scenarios, for example, managing nephrotoxins among adults of pediatric patients who already have AKI, is increasing. Depending on the type of patients, chosen digital health solution intervention, comparator groups, and selected outcomes, some of these studies showed benefits, while some did not indicate additional gain in care processes or clinical outcomes. SUMMARY: Careful needs assessment, selection of the correct digital health solution, and appropriate clinical validation of the benefits while avoiding additional health disparities are moral, professional, and ethical obligations for all individuals using these healthcare tools, including clinicians, data scientists, and administrators.

Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.

Acute kidney injury (AKI) has a significant impact on the short-term and long-term clinical outcomes of pediatric and neonatal patients, and it is imperative in these populations to mitigate the pathways leading to AKI and be prepared for early diagnosis and treatment intervention of established AKI. Recently, artificial intelligence (AI) has provided more advent predictive models for early detection/prediction of AKI utilizing machine learning (ML). By providing strong detail and evidence from risk scores and electronic alerts, this review outlines a comprehensive and holistic insight into the current state of AI in AKI in pediatric/neonatal patients. In the pediatric population, AI models including XGBoost, logistic regression, support vector machines, decision trees, naïve Bayes, and risk stratification scores (Renal Angina Index (RAI), Nephrotoxic Injury Negated by Just-in-time Action (NINJA)) have shown success in predicting AKI using variables like serum creatinine, urine output, and electronic health record (EHR) alerts. Similarly, in the neonatal population, using the "Baby NINJA" model showed a decrease in nephrotoxic medication exposure by 42%, the rate of AKI by 78%, and the number of days with AKI by 68%. Furthermore, the "STARZ" risk stratification AI model showed a predictive ability of AKI within 7 days of NICU admission of AUC 0.93 and AUC of 0.96 in the validation and derivation cohorts, respectively. Many studies have reported the superiority of using biomarkers to predict AKI in pediatric patients and neonates as well. Future directions include the application of AI along with biomarkers (NGAL, CysC, OPN, IL-18, B2M, etc.) in a Labelbox configuration to create a more robust and accurate model for predicting and detecting pediatric/neonatal AKI.

Optimizing the Design and Analysis of Future AKI Trials.

AKI is a complex clinical syndrome associated with an increased risk of morbidity and mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical trials have been inconclusive, failing to detect clinically important treatment effects at predetermined statistical thresholds. Heterogeneity in the pathobiology, etiology, presentation, and clinical course of AKI remains a key challenge in successfully testing new approaches for AKI prevention and treatment. This article, derived from the "AKI" session of the "Kidney Disease Clinical Trialists" virtual workshop held in October 2021, reviews barriers to and strategies for improving the design and implementation of clinical trials in patients with, or at risk of, developing AKI. The novel approaches to trial design included in this review span adaptive trial designs that increase the knowledge gained from each trial participant; pragmatic trial designs that allow for the efficient enrollment of sufficiently large numbers of patients to detect small, but clinically significant, treatment effects; and platform trial designs that use one trial infrastructure to answer multiple clinical questions simultaneously. This review also covers novel approaches to clinical trial analysis, such as Bayesian analysis and assessing heterogeneity in the response to therapies among trial participants. We also propose a road map and actionable recommendations to facilitate the adoption of the reviewed approaches. We hope that the resulting road map will help guide future clinical trial planning, maximize learning from AKI trials, and reduce the risk of missing important signals of benefit (or harm) from trial interventions.

Clinical Outcomes of Persistent Severe Acute Kidney Injury among Patients with Kidney Disease Improving Global Outcomes Stage 2 or 3 Acute Kidney Injury.

INTRODUCTION: The burden of persistent (≥3 days) severe AKI (PS-AKI) is poorly described among inpatients with stage 2-3 AKI in the ward or ICU. Quantification could motivate targeted interventions to decrease duration of AKI in these high-risk patients. METHODS: This retrospective cohort study included adult patients discharged from January 1, 2017, to December 31, 2019, from US hospitals in the PINC AI Healthcare Database. Patients with KDIGO stage 2 or 3 AKI, length of stay ≥3 days, ≥3 serum creatinine measures, and no history of renal transplant, dialysis, or stage 5 chronic kidney disease were included. Patients were classified as PS-AKI (stage 3 AKI lasting ≥3 days or with death in ≤3 days, or stage 2 or 3 AKI with dialysis in ≤3 days) or not PS-AKI (NPS-AKI) (stage 3 AKI for ≤2 days, or stage 2 AKI without dialysis in ≤3 days). Outcomes during index (initial) hospitalization were PS-AKI incidence, ICU use, and in-hospital mortality, and during 30 days post-discharge were readmissions, in-hospital mortality, dialysis, and "new" dialysis (dialysis among patients without dialysis during index hospitalization). For index outcomes, we used a sensitivity definition, PS-AKISens, that excluded patients who met PS-AKI criteria by dialysis/death in ≤3 days of AKI onset. Multivariable-adjusted logistic regression quantified differences between PS-AKI and NPS-AKI, overall, and separately for ICU and non-ICU patients. RESULTS: Among 126,528 inpatients with stage 2 or 3 AKI, PS-AKI developed in 24.4% (30,916), with 39% of PS-AKI occurring in non-ICU patients. With NPS-AKI as the reference group, adjusted odds ratios (aORs) (95% CI) for PS-AKI and for PS-AKISens were 2.15 (2.09-2.21) and 1.28 (1.24-1.32) for ICU use and 4.58 (4.41-4.75) and 1.79 (1.70-1.89) for in-hospital mortality during index hospitalization. For outcomes during 30 days post-discharge, aORs for PS-AKI versus NPS-AKI were 1.07 (1.02-1.11) for readmissions, 1.33 (1.18-1.49) for in-hospital mortality, 15.66 (13.87-17.67) for dialysis, and 6.80 (5.84-7.93) for new dialysis. Despite higher mortality among ICU patients, aORs for outcomes during index and 30 days post-discharge were similar for ICU and non-ICU patients. CONCLUSION: In and out of the ICU, PS-AKI frequently affected inpatients with stage 2 or 3 AKI and was independently associated with worse clinical outcomes during index hospitalization and during 30 days post-discharge. These results suggest that interventions to prevent persistence of severe AKI may reduce adverse clinical outcomes among patients with stage 2 or 3 AKI in or out of the ICU.

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.

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.

The impact of biomarkers of acute kidney injury on individual patient care.

Acute kidney injury (AKI) remains a common clinical syndrome associated with increased morbidity and mortality. In the last several years there have been several advances in the identification of patients at increased risk for AKI through the use of traditional and newer functional and damage biomarkers of AKI. This article will specifically focus on the impact of biomarkers of AKI on individual patient care, focusing predominantly on the markers with the most expansive breadth of study in patients and reported literature evidence. Several studies have demonstrated that close monitoring of widely available biomarkers such as serum creatinine and urine output is strongly associated with improved patient outcomes. An integrated approach to these biomarkers used in context with patient risk factors (identifiable using electronic health record monitoring) and with tests of renal reserve may guide implementation and targeting of care bundles to optimize patient care. Besides traditional functional markers, biochemical injury biomarkers have been increasingly utilized in clinical trials both as a measure of kidney injury as well as a trigger to initiate other treatment options (e.g. care bundles and novel therapies). As the novel measures are becoming globally available, the clinical implementation of hospital-based real-time biomarker measurements involves a multidisciplinary approach. This literature review discusses the data evidence supporting both the strengths and limitations in the clinical implementation of biomarkers based on the authors' collective clinical experiences and opinions.

Individualized acute kidney injury after care.

PURPOSE OF REVIEW: The aim of this study was to summarize the current evidence around the impact of individualizing patient care following an episode of acute kidney injury (AKI) in the ICU. RECENT FINDINGS: Over the last years, evidence has demonstrated that the follow-up care after episodes of AKI is lacking and standardization of this process is likely needed. Although this is informed largely by large retrospective cohort studies, a few prospective observational trials have been performed. Medication reconciliation and patient/caregiver education are important tenants of follow-up care, regardless of the severity of AKI. There is evidence the initiation and/or reinstitution of renin-angiotensin-aldosterone agents may improve patient's outcomes following AKI, although they may increase the risk for adverse events, especially when reinitiated early. In addition, 3 months after an episode of AKI, serum creatinine and proteinuria evaluation may help identify patients who are likely to develop progressive chronic kidney disease over the ensuing 5 years. Lastly, there are emerging differences between those who do and do not require renal replacement therapy (RRT) for their AKI, which may require more frequent and intense follow-up in those needing RRT. SUMMARY: Although large scale evidence-based guidelines are lacking, standardization of post-ICU-AKI is needed.

Assessment of provider-perceived barriers to clinical use of pharmacogenomics during participation in an institutional implementation study.

OBJECTIVE: The objective of this study was to study provider attitudes of and perceived barriers to the clinical use of pharmacogenomics before and during participation in an implementation program. PARTICIPANTS AND METHODS: From 2012 to 2017, providers were recruited. After completing semistructured interviews (SSIs) about pharmacogenomics, providers received training on and access to a clinical decision support tool housing patient-specific pharmacogenomic results. Thematic analysis of SSI was conducted (inter-rater reliability κ≥0.75). Providers also completed surveys before and during study participation, and provider-perceived barriers to pharmacogenomic implementation were analyzed. RESULTS: Seven themes emerged from the SSI (listed from most frequent to least): decision-making, concerns with pharmacogenomic adoption, outcome expectancy, provider knowledge of pharmacogenomics, patient attitudes, individualized treatment, and provider interest in pharmacogenomics. Although there was prestudy enthusiasm among all providers, concerns with clinical utility, time, results accession, and knowledge of pharmacogenomics were frequently stated at baseline. Despite this, adoption of pharmacogenomics was robust, as patient-specific results were accessed at 64% of visits, and medication changes were influenced by provided pharmacogenomic information 42% of the time. Providers reported they had enough time to evaluate the information and the results were easily understood on 74 and 98% of surveys, respectively. Nevertheless, providers consistently felt there was insufficient pharmacogenomic information for most drugs they prescribed and clear guidelines for using pharmacogenomic information were lacking. CONCLUSION: Despite initial concerns about adequate time and knowledge for adoption, providers frequently utilized pharmacogenomic results. Provider-perceived barriers to wider use included lack of clear guidelines and evidence for most drugs, highlighting important considerations for the field of pharmacogenomics.

Use of Cell Cycle Arrest Biomarkers in Conjunction With Classical Markers of Acute Kidney Injury.

OBJECTIVES: Decreased urine output and/or increased serum creatinine may herald the development of acute kidney injury or reflect normal physiology. In this secondary analysis of the Sapphire study, we examined biomarkers of cell cycle arrest in the settings of oliguria and/or azotemia to improve risk assessment when used with conventional indices in predicting severe acute kidney injury (Kidney Disease: Improving Global Outcomes 3 defined by the need for renal replacement therapy or changes in urine output, serum creatinine or both) or death. DESIGN: Prospective, international, Sapphire study. SETTING: Academic Medical Center. PATIENTS: Patients without acute kidney injury Kidney Disease: Improving Global Outcomes stage 2 or 3. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary endpoint being development of severe acute kidney injury or death within 1 week. Secondary analysis examined the relationship between tissue inhibitor of metalloproteinases-2 ([TIMP-2]) and insulin growth factor binding protein 7 ([IGFBP7]) and 9-month death or dialysis conditioned on progression to stage 2-3 acute kidney injury within 1 week. Seventy-nine patients reached the primary endpoint and were more likely to be surgical, with higher nonrenal Acute Physiology and Chronic Health Evaluation III scores and more chronic kidney disease. Stage 1 urine output, serum creatinine, and urinary [TIMP-2]•[IGFBP7] greater than 2.0 were all predictive of progression to the primary endpoint independent from nonrenal Acute Physiology and Chronic Health Evaluation III score. Combinations of predictors increased the hazard ratios considerably (from 2.17 to 4.14 to 10.05, respectively). In the presence of acute kidney injury (stage 1), [TIMP-2]•[IGFBP7] greater than 2.0 leads to an increased risk of death or dialysis at 9 months even in the absence of progression of acute kidney injury (stage 2-3) within 7 days. CONCLUSIONS: Cell cycle arrest biomarkers, TIMP-2 and IGFBP7, improve risk stratification for severe outcomes in patients with stage 1 acute kidney injury by urine output, serum creatinine or both, with risk increasing with each acute kidney injury indicator. Longer term outcomes demonstrate that the associated risks of a [TIMP-2]•[IGFBP7] greater than 2.0 is equivalent to acute kidney injury progression even where no progression from stage 1 acute kidney injury is observed.

Patient-provider communications about pharmacogenomic results increase patient recall of medication changes.

Effective doctor-patient communication is critical for disease management, especially when considering genetic information. We studied patient-provider communications after implementing a point-of-care pharmacogenomic results delivery system to understand whether pharmacogenomic results are discussed and whether medication recall is impacted. Outpatients undergoing preemptive pharmacogenomic testing (cases), non-genotyped controls, and study providers were surveyed from October 2012-May 2017. Patient responses were compared between visits where pharmacogenomic results guided prescribing versus visits where pharmacogenomics did not guide prescribing. Provider knowledge of pharmacogenomics, before and during study participation, was also analyzed. Both providers and case patients frequently reported discussions of genetic results after visits where pharmacogenomic information guided prescribing. Importantly, medication changes from visits where pharmacogenomics influenced prescribing were more often recalled than non-pharmacogenomic guided medication changes (OR = 3.3 [1.6-6.7], p = 0.001). Case patients who had separate visits where pharmacogenomics did and did not, respectively, influence prescribing more often remembered medication changes from visits where genomic-based guidance was used (OR = 3.4 [1.2-9.3], p = 0.02). Providers also displayed dramatic increases in personal genomic understanding through program participation (94% felt at least somewhat informed about pharmacogenomics post-participation, compared to 61% at baseline, p = 0.04). Using genomic information during prescribing increases patient-provider communications, patient medication recall, and provider understanding of genomics, important ancillary benefits to clinical use of pharmacogenomics.