Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference

Adult Cardiac Surgery-Associated Acute Kidney Injury: Joint Consensus Report

OBJECTIVES

Acute kidney injury (AKI) is increasingly recognized as a source of poor patient outcomes after cardiac surgery. The purpose of the present report is to provide perioperative teams with expert recommendations specific to cardiac surgery-associated AKI (CSA-AKI).

METHODS

This report and consensus recommendations were developed during a joint, in-person, multidisciplinary conference with the Perioperative Quality Initiative and the Enhanced Recovery After Surgery Cardiac Society. Multinational practitioners with diverse expertise in all aspects of cardiac surgical perioperative care, including clinical backgrounds in anesthesiology, surgery and nursing, met from October 20 to 22, 2021, in Sacramento, California, and used a modified Delphi process and a comprehensive review of evidence to formulate recommendations. The quality of evidence and strength of each recommendation were established using the Grading of Recommendations Assessment, Development, and Evaluation methodology. A majority vote endorsed recommendations.

RESULTS

Based on available evidence and group consensus, a total of 13 recommendations were formulated (4 for the preoperative phase, 4 for the intraoperative phase, and 5 for the postoperative phase), and are reported here.

CONCLUSIONS

Because there are no reliable or effective treatment options for CSA-AKI, evidence-based practices that highlight prevention and early detection are paramount. Cardiac surgery-associated AKI incidence may be mitigated and postsurgical outcomes improved by focusing additional attention on presurgical kidney health status; implementing a specific cardiopulmonary bypass bundle; using strategies to maintain intravascular euvolemia; leveraging advanced tools such as the electronic medical record, point-of-care ultrasound, and biomarker testing; and using patient-specific, goal-directed therapy to prioritize oxygen delivery and end-organ perfusion over static physiologic metrics.

Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is a common complication in sepsis. However, the trajectories of sepsis-induced AKI and their transcriptional profiles are not well characterized.

METHODS

Sepsis patients admitted to centres participating in Chinese Multi-omics Advances In Sepsis (CMAISE) from November 2020 to December 2021 were enrolled, and gene expression in peripheral blood mononuclear cells was measured on Day 1. The renal function trajectory was measured by the renal component of the SOFA score (SOFA_renal) on Days 1 and 3. Transcriptional profiles on Day 1 were compared between these renal function trajectories, and a support vector machine (SVM) was developed to distinguish transient from persistent AKI.

RESULTS

A total of 172 sepsis patients were enrolled during the study period. The renal function trajectory was classified into four types: non-AKI (SOFA_renal = 0 on Days 1 and 3, n = 50), persistent AKI (SOFA_renal > 0 on Days 1 and 3, n = 62), transient AKI (SOFA_renal > 0 on Day 1 and SOFA_renal = 0 on Day 3, n = 50) and worsening AKI (SOFA_renal = 0 on Days 1 and SOFA_renal > 0 on Day 3, n = 10). The persistent AKI group showed severe organ dysfunction and prolonged requirements for organ support. The worsening AKI group showed the least organ dysfunction on day 1 but had higher serum lactate and prolonged use of vasopressors than the non-AKI and transient AKI groups. There were 2091 upregulated and 1,902 downregulated genes (adjusted p < 0.05) between the persistent and transient AKI groups, with enrichment in the plasma membrane complex, receptor complex, and T-cell receptor complex. A 43-gene SVM model was developed using the genetic algorithm, which showed significantly greater performance predicting persistent AKI than the model based on clinical variables in a holdout subset (AUC: 0.948 [0.912, 0.984] vs. 0.739 [0.648, 0.830]; p < 0.01 for Delong's test).

CONCLUSIONS

Our study identified four subtypes of sepsis-induced AKI based on kidney injury trajectories. The landscape of host response aberrations across these subtypes was characterized. An SVM model based on a gene signature was developed to predict renal function trajectories, and showed better performance than the clinical variable-based model. Future studies are warranted to validate the gene model in distinguishing persistent from transient AKI.

Association between nitric oxide synthase 3 genetic variant and acute kidney injury following pediatric cardiac surgery

BACKGROUND

Acute kidney injury (AKI) complicates 30% to 50% of cardiac surgeries in pediatric patients. Genetic variants that affect renal blood flow and inflammation have been associated with AKI after cardiac surgery in diverse populations of adults but have not been studied in children. The objective of this study is to test the hypothesis that common candidate genetic variants are associated with AKI following pediatric cardiac surgery.

METHODS

This is a retrospective cohort study at a single tertiary referral children's hospital of 2,062 individual patients undergoing surgery for congenital heart disease from September 2007 to July 2020. Pre-specified variants in candidate genes (AGTR1, APOE, IL6, NOS3, and TNF) were chosen. AKI was defined using Kidney Disease: Improving Global Outcomes serum creatinine criteria in the first week following surgery. Outcomes were analyzed by univariate and multivariable analysis of demographic, clinical, and genetic factors.

RESULTS

The study population had median age of 6 (interquartile range [IQR], 1-53) months, 759 (37%) of whom met criteria for postoperative AKI. In unadjusted analyses of each genetic variant, only NOS3 (rs2070744) was associated with lower risk for AKI (OR 0.75, 95% CI 0.62-0.9, P = .002). In logistic regression analyses adjusting for body surface area, previously identified genetic syndrome, Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery (STAT) score, cardiopulmonary bypass time, and nephrotoxic medication exposure, the NOS3 variant remained protective against AKI (OR 0.7, 95% CI 0.58-0.85, P<.001).

CONCLUSIONS

A common variant in NOS3 is associated with decreased incidence of AKI in children undergoing cardiac surgery. Further analysis of the genetic contributions to postoperative AKI may help identify individual risk in the pediatric population.

The rate of acute kidney injury (AKI) alert detection by the attending physicians was associated with the prognosis of patients with AKI

Introduction

Early identification of AKI was always considered to improve patients' prognosis. Some studies found that AKI early warning tools didn't affect patients' prognosis. Therefore, additional studies were necessary to explore the reasons.

Methods

This study was a secondary analysis of a multicenter randomized controlled trial that found electronic health record warnings for AKI did not influence patients' prognoses. Univariate, multivariate, subgroup, curve fitting, and threshold effect analysis were used to explore the association between AKI warnings detected by attending physicians and the patient's prognosis.

Results

A total of 6,030 AKI patients were included in the study. The patients were classified into two groups based on the rate of AKI alerts detected by attending physicians: the partial group (n = 5,377), and the complete group (n = 653). In comparison to the partial group, the complete group significantly decreased 14-day AKI progression, 14-day dialysis, and 14-day mortality, with adjusted ORs of 0.48 (0.33, 0.70), 0.26 (0.09, 0.77), and 0.53 (0.33, 0.84) respectively, and the complete group significantly improve the discharge to home, with an OR value of 1.50 (1.21, 1.87). When the rate of AKI alerts detected by the attending physicians as a continuity variable, we found that the rate of alerts seen by attending physicians was associated with 14-day mortality and the discharge to home, with adjusted ORs of 1.76 (1.11, 2.81) and 1.42 (1.13, 1.80). The sensitivity analysis, curve-fitting analysis, and threshold effect analysis also showed that the rate of alert seen by the attending physician was correlated with the patient's prognosis.

Conclusion

The rate of AKI alert detection by attending physician were related to the patient's prognosis. The higher the rate of AKI alert detection by attending physicians, the better the prognosis of patients with AKI.

Assessment of knowledge of acute kidney injury among non-nephrology healthcare workers in North-Kivu Province, Democratic Republic of the Congo

Background: Assessment of knowledge of acute kidney injury (AKI) among healthcare workers (HCWs) is necessary to identify areas of deficiency and key topics to focus on while organizing educational programs to improve AKI care. The objective of this study was to assess AKI knowledge and practice among health care providers in North Kivu province, the eastern Democratic Republic of the Congo. Material and methods: This was a cross-sectional study conducted in six public hospitals in North Kivu province using a self-administered questionnaire. Results: A total of 158 HCWs completed the survey, among them 66 (41.78%) were physicians. The mean age of respondents was 36.07 ± 10.16 years and the male gender was 56.33%. Only 12 (7.59%) of the respondents had a good knowledge of the definition and classification of AKI. The respondents’ mean scores were 6.76 out of a total of 18 about risk factors for AKI and 6.29 out of a total of 11 with regard to nephrotoxic drugs. Regarding practices, 28.48% of the respondents assess the risk of AKI in their patients in their daily practices; 31.65% report AKI in the patients’ medical history, and 33.54% call on a nephrologist specialist to get specialized advice. Conclusion: This study found considerable gaps in knowledge and practice regarding AKI among most of HCWs in North Kivu province.

Real-world Health Data and Precision for the Diagnosis of Acute Kidney Injury, Acute-on-Chronic Kidney Disease, and Chronic Kidney Disease: Observational Study

Background

The criteria for the diagnosis of kidney disease outlined in the Kidney Disease: Improving Global Outcomes guidelines are based on a patient’s current, historical, and baseline data. The diagnosis of acute kidney injury, chronic kidney disease, and acute-on-chronic kidney disease requires previous measurements of creatinine, back-calculation, and the interpretation of several laboratory values over a certain period. Diagnoses may be hindered by unclear definitions of the individual creatinine baseline and rough ranges of normal values that are set without adjusting for age, ethnicity, comorbidities, and treatment. The classification of correct diagnoses and sufficient staging improves coding, data quality, reimbursement, the choice of therapeutic approach, and a patient’s outcome.

Objective

In this study, we aim to apply a data-driven approach to assign diagnoses of acute, chronic, and acute-on-chronic kidney diseases with the help of a complex rule engine.

Methods

Real-time and retrospective data from the hospital’s clinical data warehouse of inpatient and outpatient cases treated between 2014 and 2019 were used. Delta serum creatinine, baseline values, and admission and discharge data were analyzed. A Kidney Disease: Improving Global Outcomes–based SQL algorithm applied specific diagnosis-based International Classification of Diseases (ICD) codes to inpatient stays. Text mining on discharge documentation was also conducted to measure the effects on diagnosis.

Results

We show that this approach yielded an increased number of diagnoses (4491 cases in 2014 vs 11,124 cases of ICD-coded kidney disease and injury in 2019) and higher precision in documentation and coding. The percentage of unspecific ICD N19-coded diagnoses of N19 codes generated dropped from 19.71% (1544/7833) in 2016 to 4.38% (416/9501) in 2019. The percentage of specific ICD N18-coded diagnoses of N19 codes generated increased from 50.1% (3924/7833) in 2016 to 62.04% (5894/9501) in 2019.

Conclusions

Our data-driven method supports the process and reliability of diagnosis and staging and improves the quality of documentation and data. Measuring patient outcomes will be the next step in this project.

Integrating electronic health data records to develop and validate a predictive model of hospital-acquired acute kidney injury in non-critically ill patients

Background

Models developed to predict hospital-acquired acute kidney injury (HA-AKI) in non-critically ill patients have a low sensitivity, do not include dynamic changes of risk factors and do not allow the establishment of a time relationship between exposure to risk factors and AKI. We developed and externally validated a predictive model of HA-AKI integrating electronic health databases and recording the exposure to risk factors prior to the detection of AKI.

Methods

The study set was 36 852 non-critically ill hospitalized patients admitted from January to December 2017. Using stepwise logistic analyses, including demography, chronic comorbidities and exposure to risk factors prior to AKI detection, we developed a multivariate model to predict HA-AKI. This model was then externally validated in 21 545 non-critical patients admitted to the validation centre in the period from June 2017 to December 2018.

Results

The incidence of AKI in the study set was 3.9%. Among chronic comorbidities, the highest odds ratios (ORs) were conferred by chronic kidney disease, urologic disease and liver disease. Among acute complications, the highest ORs were associated with acute respiratory failure, anaemia, systemic inflammatory response syndrome, circulatory shock and major surgery. The model showed an area under the curve (AUC) of 0.907 [95% confidence interval (CI) 0.902–0.908), a sensitivity of 82.7 (95% CI 80.7–84.6) and a specificity of 84.2 (95% CI 83.9–84.6) to predict HA-AKI, with an adequate goodness-of-fit for all risk categories (χ² = 6.02, P = 0.64). In the validation set, the prevalence of AKI was 3.2%. The model showed an AUC of 0.905 (95% CI 0.904–0.910), a sensitivity of 81.2 (95% CI 79.2–83.1) and a specificity of 82.5 (95% CI 82.2–83) to predict HA-AKI and had an adequate goodness-of-fit for all risk categories (χ² = 4.2, P = 0.83). An online tool (predaki.amalfianalytics.com) is available to calculate the risk of AKI in other hospital environments.

Conclusions

By using electronic health data records, our study provides a model that can be used in clinical practice to obtain an accurate dynamic and updated assessment of the individual risk of HA-AKI during the hospital admission period in non-critically ill patients.

Ambiguous definitions for baseline serum creatinine affect acute kidney diagnosis at the emergency department

Background

Acute kidney injury (AKI) incidence is increasing, however AKI is often missed at the emergency department (ED). AKI diagnosis depends on changes in kidney function by comparing a serum creatinine (SCr) measurement to a baseline value. However, it remains unclear to what extent different baseline values may affect AKI diagnosis at ED.

Methods

Routine care data from ED visits between 2012 and 2019 were extracted from the Utrecht Patient Oriented Database. We evaluated baseline definitions with criteria from the RIFLE, AKIN and KDIGO guidelines. We evaluated four baseline SCr definitions (lowest, most recent, mean, median), as well as five different time windows (up to 365 days prior to ED visit) to select a baseline and compared this to the first measured SCr at ED. As an outcome, we assessed AKI prevalence at ED.

Results

We included 47,373 ED visits with both SCr-ED and SCr-BL available. Of these, 46,100 visits had a SCr-BL from the − 365/− 7 days time window. Apart from the lowest value, AKI prevalence remained similar for the other definitions when varying the time window. The lowest value with the − 365/− 7 time window resulted in the highest prevalence (21.4%). Importantly, applying the guidelines with all criteria resulted in major differences in prevalence ranging from 5.9 to 24.0%.

Conclusions

AKI prevalence varies with the use of different baseline definitions in ED patients. Clinicians, as well as researchers and developers of automatic diagnostic tools should take these considerations into account when aiming to diagnose AKI in clinical and research settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02581-x.

The Impact of Outpatient Laboratory Alerting Mechanisms in Patients with AKI

Background

AKI is an abrupt decrease in kidney function associated with significant morbidity and mortality. Electronic notifications of AKI have been utilized in patients who are hospitalized, but their efficacy in the outpatient setting is unclear.

Methods

We evaluated the effect of two outpatient interventions: an automated comment on increasing creatinine results (intervention I; 6 months; n=159) along with an email to the provider (intervention II; 3 months; n=105), compared with a control (baseline; 6 months; n=176). A comment was generated if a patient's creatinine increased by >0.5 mg/dl (previous creatinine ≤2.0 mg/dl) or by 50% (previous creatinine >2.0 mg/dl) within 180 days. Process measures included documentation of AKI and clinical actions. Clinical outcomes were defined as recovery from AKI within 7 days, prolonged AKI from 8 to 89 days, and progression to CKD with in 120 days.

Results

Providers were more likely to document AKI in interventions I (P=0.004; OR, 2.80; 95% CI, 1.38 to 5.67) and II (P=0.01; OR, 2.66; 95% CI, 1.21 to 5.81). Providers were also more likely to discontinue nephrotoxins in intervention II (P<0.001; OR, 4.88; 95% CI, 2.27 to 10.50). The median time to follow-up creatinine trended shorter among patients with AKI documented (21 versus 42 days; P=0.11). There were no significant differences in clinical outcomes.

Conclusions

An automated comment was associated with improved documented recognition of AKI and the additive intervention of an email alert was associated with increased discontinuation of nephrotoxins, but neither improved clinical outcomes. Translation of these findings into improved outcomes may require corresponding standardization of clinical practice protocols for managing AKI.

Development and Validation of a Model to Predict Severe Hospital-Acquired Acute Kidney Injury in Non-Critically Ill Patients

BACKGROUND

The current models developed to predict hospital-acquired AKI (HA-AKI) in non-critically ill fail to identify the patients at risk of severe HA-AKI stage 3.

OBJECTIVE

To develop and externally validate a model to predict the individual probability of developing HA-AKI stage 3 through the integration of electronic health databases.

METHODS

Study set: 165,893 non-critically ill hospitalized patients. Using stepwise logistic regression analyses, including demography, chronic comorbidities, and exposure to risk factors prior to AKI detection, we developed a multivariate model to predict HA-AKI stage 3. This model was then externally validated in 43,569 non-critical patients admitted to the validation center.

RESULTS

The incidence of HA-AKI stage 3 in the study set was 0.6%. Among chronic comorbidities, the highest odds ratios were conferred by ischemic heart disease, ischemic cerebrovascular disease, chronic congestive heart failure, chronic obstructive pulmonary disease, chronic kidney disease and liver disease. Among acute complications, the highest odd ratios were associated with acute respiratory failure, major surgery and exposure to nephrotoxic drugs. The model showed an AUC of 0.906 (95% CI 0.904 to 0.908), a sensitivity of 89.1 (95% CI 87.0-91.0) and a specificity of 80.5 (95% CI 80.2-80.7) to predict HA-AKI stage 3, but tended to overestimate the risk at low-risk categories with an adequate goodness-of-fit for all risk categories (Chi2: 16.4, p: 0.034). In the validation set, incidence of HA-AKI stage 3 was 0.62%. The model showed an AUC of 0.861 (95% CI 0.859-0.863), a sensitivity of 83.0 (95% CI 80.5-85.3) and a specificity of 76.5 (95% CI 76.2-76.8) to predict HA-AKI stage 3 with an adequate goodness of fit for all risk categories (Chi2: 15.42, p: 0.052).

CONCLUSIONS

Our study provides a model that can be used in clinical practice to obtain an accurate dynamic assessment of the individual risk of HA-AKI stage 3 along the hospital stay period in non-critically ill patients.

Rational selection of a biomarker panel targeting unmet clinical needs in kidney injury

The pipeline of biomarker translation from bench to bedside is challenging and limited biomarkers have been adopted to routine clinical care. Ideally, biomarker research and development should be driven by unmet clinical needs in health care. To guide researchers, clinical chemists and clinicians in their biomarker research, the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has developed a structured questionnaire in which the clinical gaps in current clinical pathways are identified and desirable performance specifications are predefined. In kidney injury, the high prevalence of the syndrome acute kidney injury (AKI) in the hospital setting has a significant impact on morbidity, patient survival and health care costs, but the use of biomarkers indicating early kidney injury in daily patient care remains limited. Routinely, medical labs measure serum creatinine, which is a functional biomarker, insensitive for detecting early kidney damage and cannot distinguish between renal and prerenal AKI. The perceived unmet clinical needs in kidney injury were identified through the EFLM questionnaire. Nephrologists within our tertiary care hospital emphasized that biomarkers are needed for (1) early diagnosis of in-hospital AKI after a medical insult and in critically ill patients, (2) risk stratification for kidney injury prior to a scheduled (elective) intervention, (3) kidney injury monitoring in patients scheduled to receive nephrotoxic medication and after kidney transplantation and (4) differentiation between prerenal AKI and structural kidney damage. The biomarker search and selection strategy resulted in a rational selection of an eleven-protein urinary panel for kidney injury that target these clinical needs. To assess the clinical utility of the proposed biomarker panel in kidney injury, a multiplexed LC-MS test is now in development for the intended translational research.

A Review on the Application and Limitations of Administrative Health Care Data for the Study of Acute Kidney Injury Epidemiology and Outcomes in Children

Administrative health care databases contain valuable patient information generated by health care encounters. These "big data" repositories have been increasingly used in epidemiological health research internationally in recent years as they are easily accessible and cost-efficient and cover large populations for long periods. Despite these beneficial characteristics, it is also important to consider the limitations that administrative health research presents, such as issues related to data incompleteness and the limited sensitivity of the variables. These barriers potentially lead to unwanted biases and pose threats to the validity of the research being conducted. In this review, we discuss the effectiveness of health administrative data in understanding the epidemiology of and outcomes after acute kidney injury (AKI) among adults and children. In addition, we describe various validation studies of AKI diagnostic or procedural codes among adults and children. These studies reveal challenges of AKI research using administrative data and the lack of this type of research in children and other subpopulations. Additional pediatric-specific validation studies of administrative health data are needed to promote higher volume and increased validity of this type of research in pediatric AKI, to elucidate the large-scale epidemiology and patient and health systems impacts of AKI in children, and to devise and monitor programs to improve clinical outcomes and process of care.

For Whom the Bell Tolls: Acute Kidney Injury and Electronic Alerts for the Pediatric Nephrologist

With the advent of the electronic medical record, automated alerts have allowed for improved recognition of patients with acute kidney injury (AKI). Pediatric patients have the opportunity to benefit from such alerts, as those with a diagnosis of AKI are at risk of developing long-term consequences including reduced renal function and hypertension. Despite extensive studies on the implementation of electronic alerts, their overall impact on clinical outcomes have been unclear. Understanding the results of these studies have helped define best practices in developing electronic alerts with the aim of improving their impact on patient care. As electronic alerts for AKI are applied to pediatric patients, identifying their strengths and limitations will allow for continued improvement in its use and efficacy.

Frequency of Exposure of Nephrotoxic Drugs and Drug-Induced Acute Kidney Injury in Pediatric Intensive Care Unit: A Retrospective Review From a Tertiary Care Centre in Pakistan

Introduction

Acute kidney injury (AKI) is one of the most common problems seen in the pediatric intensive care unit (PICU), with an overall 27% incidence. Besides many other factors, nephrotoxic medications (Nephrotoxins; Ntx) are also responsible for a large proportion of potentially avoidable pediatric AKI, directly accounting for 16% of AKI events.

Objective

To assess potential associations between nephrotoxic drugs and the risk of developing AKI in children admitted in PICU.

Material and methods

This is a retrospective cross-sectional study. Children (aged 1 month - 18 years) admitted to the PICU, with a length of stay >24 hours, were included. AKI was defined as according to KDIGO (Kidney Disease Improving Global Outcomes) criteria. Mild AKI was defined as a rise in creatinine value of 0.3 mg/dl from presenting value at a 24-hour interval. Patients were grouped according to the presence or absence of AKI. All medications administered in the ICU were assessed for nephrotoxicity through a review of adverse reactions mentioned in the Pediatric Dosage Handbook, along with consultation with a clinical pharmacist.

Results

Among 752 patients, the mean age was 4.8 years ± 4.37. There were 57.3% male and 42.7% female children. Among the exposed children, 37.4% received one drug, 32.4% received two drugs and 12.1% had high nephrotoxin exposure. The most commonly used drug was vancomycin (16.8%), as a single Ntx; vancomycin/colistin (12.9%), in dual nephrotoxic combination; and vancomycin/colistin/amphotericin (2.9%) in highly exposed children (i.e., with equal or more than three). Overall, the incidence of AKI was 14.9%.

Conclusion

Nephrotoxins are potentially avoidable risk factors in critically ill children. Whenever a combination of medications is required, it’s advisable to review all medications for better protection of kidneys and preventing of acute kidney injury.

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.

Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury

Background

Acute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations.

Methods

We developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set.

Results

Considerations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients.

Conclusions

Development and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care.

Acute kidney injury demographics and outcomes: changes following introduction of electronic acute kidney injury alerts-an analysis of a national dataset

BACKGROUND

Electronic alerts for acute kidney injury (AKI) have been widely advocated. Our aim was to describe the changes in AKI demographics and outcomes following implementation of a national electronic AKI alert programme.

METHODS

A prospective national cohort study was undertaken to collect data on all cases of AKI in adult patients (≥18 years of age) between 1 April 2015 and 31 March 2019.

RESULTS

Over the period of data collection, there were 193 838 AKI episodes in a total of 132 599 patients. The lowest incidence of AKI was seen in the first year after implementation of electronic alerts. A 30-day mortality was highest in Year 1 and significantly lower in all subsequent years. A direct comparison of mortality in Years 1 and 4 demonstrated a significantly increased relative risk (RR) of death in Year 1: RR = 1.08 [95% confidence interval (CI) 1.054-1.114 P < 0.001]. This translates into a number needed to treat in Year 4 for one additional patient to survive of 69.5 (95% CI 51.7-106.2) when directly comparing the outcomes across the 2 years. The increase in the number of cases and improved outcomes was more pronounced in community-acquired AKI, and was associated with a significant increase in patient hospitalization.

CONCLUSIONS

This study represents the first large-scale dataset to clearly demonstrate that a national AKI alerting system which highlights AKI is associated with a change in both AKI demographics and patient outcomes.

Impact of acute kidney injury and nephrotoxic exposure on hospital length of stay

OBJECTIVE

Acute kidney injury (AKI) is a common occurrence among hospitalized children and leads to increased mortality and prolonged length of stay (LOS) in critically ill patients. Few studies have examined the impact of AKI on LOS for common pediatric conditions. We hypothesized that a diagnosis of AKI would be associated with a longer hospital LOS and increased exposure to nephrotoxic medications for all patients.

PATIENTS AND METHODS

We performed a multicenter retrospective cross-sectional analysis of 34 children's hospitals in the Pediatric Health Information System (PHIS) database from 1/2009 through 12/2013. Patients were grouped based on primary discharge diagnosis, number of days spent in an intensive care unit, and assignment of a secondary diagnostic code for AKI. Median LOS was compared among different patient groupings. Exposure to commonly used nephrotoxic medications was collected for each admission.

RESULTS

A total of 588,884 admissions from 423,337 patients were included in the analysis. The median LOS among non-critically ill patients with and without AKI was 5 days [95% CI 3-10] versus 2 days [95% CI 1-4], respectively. Among critically ill patients, median LOS for those with and without AKI was 12 days [95% CI 7-20] versus 4 days [95% CI 2-7], respectively. Patients who developed AKI were more likely to have significant nephrotoxic exposure.

CONCLUSIONS

Development of AKI was associated with longer hospital length of stay and increased nephrotoxic medication exposure for all diagnostic categories. Non-critically ill children with AKI were hospitalized the same length or longer than critically ill children without AKI.

Artificial Intelligence in Acute Kidney Injury Risk Prediction

Acute kidney injury (AKI) is a frequent complication in hospitalized patients, which is associated with worse short and long-term outcomes. It is crucial to develop methods to identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clinical informatics and the increasing availability of electronic medical records have allowed for the development of artificial intelligence predictive models of risk estimation in AKI. In this review, we discussed the progress of AKI risk prediction from risk scores to electronic alerts to machine learning methods.

Acute kidney injury risk-based screening in pediatric inpatients: a pragmatic randomized trial

BACKGROUND

Pediatric acute kidney injury (AKI) is common and associated with increased morbidity, mortality, and length of stay. We performed a pragmatic randomized trial testing the hypothesis that AKI risk alerts increase AKI screening.

METHODS

All intensive care and ward admissions of children aged 28 days through 21 years without chronic kidney disease from 12/6/2016 to 11/1/2017 were included. The intervention alert displayed if calculated AKI risk was > 50% and no serum creatinine (SCr) was ordered within 24 h. The primary outcome was SCr testing within 48 h of AKI risk > 50%.

RESULTS

Among intensive care admissions, 973/1909 (51%) were randomized to the intervention. Among those at risk, more SCr tests were ordered for the intervention group than for controls (418/606, 69% vs. 361/597, 60%, p = 0.002). AKI incidence and severity were the same in intervention and control groups. Among ward admissions, 5492/10997 (50%) were randomized to the intervention, and there were no differences between groups in SCr testing, AKI incidence, or severity of AKI.

CONCLUSIONS

Alerts based on real-time prediction of AKI risk increased screening rates in intensive care but not pediatric ward settings. Pragmatic clinical trials provide the opportunity to assess clinical decision support and potentially eliminate ineffective alerts.

Acute kidney injury

Acute kidney injury (AKI) is defined by a rapid increase in serum creatinine, decrease in urine output, or both. AKI occurs in approximately 10-15% of patients admitted to hospital, while its incidence in intensive care has been reported in more than 50% of patients. Kidney dysfunction or damage can occur over a longer period or follow AKI in a continuum with acute and chronic kidney disease. Biomarkers of kidney injury or stress are new tools for risk assessment and could possibly guide therapy. AKI is not a single disease but rather a loose collection of syndromes as diverse as sepsis, cardiorenal syndrome, and urinary tract obstruction. The approach to a patient with AKI depends on the clinical context and can also vary by resource availability. Although the effectiveness of several widely applied treatments is still controversial, evidence for several interventions, especially when used together, has increased over the past decade.

A Survey Study of Self-Rated Patients' Knowledge About AKI in a Post-Discharge AKI Clinic

BACKGROUND

Survivors of acute kidney injury (AKI) are at risk of adverse outcomes. Post-discharge nephrology care may improve patients' AKI knowledge and prevent post-AKI complications.

OBJECTIVE

The purpose of this study was to examine patients' awareness about their AKI diagnosis and self-rated knowledge and severity of AKI before and after their first post-discharge AKI Clinic encounter.

DESIGN

We conducted a pre- and post-survey study among AKI survivors who attended a post-discharge AKI Clinic.

SETTING

AKI Clinic at the University of Kentucky Medical Center (October 2016 to December 2017). Education about AKI was based on transformative learning theory and provided through printed materials and interdisciplinary interactions between patients/caregivers and nurses, pharmacists, and nephrologists.

PATIENTS

A total of 104 patients completed the survey and were included in the analysis.

MEASUREMENTS

Three survey questions were administered before and after the first AKI Clinic encounter: Question 1 (yes-no) for awareness, and questions 2 and 3 (Likert scale, 1 = lowest to 5 = highest) for self-rated knowledge and severity of AKI.

METHODS

Two mixed-model analysis of variance (ANOVA) was used for between-group (AKI severity) and within-group (pre- and post-encounter) comparisons. Logistic regression was used to examine parameters associated with the within-group change in self-perceived knowledge.

RESULTS

Twenty-two out of 104 (21%) patients were not aware of their AKI diagnosis before the clinic encounter. Patients' self-ratings of their AKI knowledge significantly increased after the first AKI Clinic encounter (mean ± SEM: pre-visit = 1.94 ± 0.12 to post-visit = 3.88 ± 0.09, P = .001), even after adjustment for age, gender, Kidney Disease Improving Global Outcomes (KDIGO) severity stage, or poverty level. Patients with AKI stage 3 self-rated their AKI as more severe than patients with AKI stage 1 or 2.

LIMITATIONS

Our study population may not be representative of the general AKI survivor population. Administered surveys are subject to response-shift bias.

CONCLUSIONS

Patients' self-perceived knowledge about AKI significantly increased following the first post-discharge AKI Clinic encounter that included interdisciplinary education. This is the first survey study examining self-perceived AKI knowledge in AKI survivors. Further examination of AKI literacy in survivors of AKI and its effect on post-AKI outcomes is needed.

TRIAL REGISTRATION

Not applicable.

Big Data and Pediatric Acute Kidney Injury: The Promise of Electronic Health Record Systems

Over the last decade, our understanding of acute kidney injury (AKI) has evolved considerably. The development of a consensus definition standardized the approach to identifying and investigating AKI in children. As a result, pediatric AKI epidemiology has been refined and the consequences of renal injury are better established. Similarly, "big data" methodologies experienced a dramatic evolution and maturation, leading the critical care community to explore potential AKI/big data synergies. One such concept with tremendous potential is electronic health record (EHR) enabled informatics. Much of the promise surrounding these approaches is due to the unique position of the EHR which sits at the intersection of data accumulation and care delivery. EHR data is generated simply via the provision of routine clinical care and should be considered "big" from the standpoint of volume, variety, and velocity as a myriad of diverse elements accumulate rapidly in real time, spontaneously generating an immense dataset. This massive dataset interfaces directly with providers which creates tremendous opportunity. AKI can be diagnosed more accurately, AKI-related care can be optimized, and subsequent outcomes can be improved. Although applying big data concepts to the EHR has proven more challenging than originally thought, we have seen much success and continue to explore its potential. In this review article, we will discuss the EHR in the context of big data concepts, describe approaches applied to date, examine the challenges surrounding optimal application, and explore future directions.

Improving clinical prediction rules in acute kidney injury with the use of biomarkers of cell cycle arrest: a pilot study

INTRODUCTION

Early recognition of patients developing acute kidney injury (AKI) is of considerable interest, we report the first use of a combination of a clinical prediction rule with a biomarker in emergent adult medical patients to improve AKI recognition.

METHODS

Single-centre prospective pilot study of medical admissions without AKI identified as high risk by a clinical prediction rule. Urine samples were obtained and tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) - biomarkers associated with cell cycle arrest, were measured.

OUTCOME

Creatinine-based KDIGO hospital-acquired AKI (HA-AKI).

RESULTS

Of 69 patients recruited, HA-AKI developed in 13% (n = 9), in whom biomarker values were higher (median 0.43 (interquartile range (IQR) 0.21-1.25) vs. 0.07 (0.03-0.16) in cases without (p = 0.008). Peak rise in creatinine was higher in biomarker positive cases (median 30 μmol/L (7-72) vs. 1 μmol/L (0-16), p = 0.002). AUROC was 0.78 (95% CI 0.57-0.98). At the suggested cut-off (0.3) sensitivity for predicting AKI was 78% (95% CI 40-97%), specificity 89% (78-95%), positive predictive value 50% (31-69%) and negative predictive value 96% (89-99%).

DISCUSSION

Addition of a urinary biomarker allows exclusion of a significant number of patients identified to be at higher risk of AKI by a clinical prediction rule.

Impact of Daily Electronic Laboratory Alerting on Early Detection and Clinical Documentation of Acute Kidney Injury in Hospital Settings

Acute kidney injury, especially early-stage disease, is a common hospital comorbidity requiring timely recognition and treatment. We investigated the effect of daily laboratory alerting of patients at risk for acute kidney injury as measured by documented International Classification of Diseases diagnoses. A quasi-experimental study was conducted at 8 New York hospitals between January 1, 2014, and June 30, 2017. Education of clinical documentation improvement specialists, physicians, and nurses was conducted from July 1, 2014, to December 31, 2014, prior to initiating daily hospital-wide laboratory acute kidney injury alerting on January 1, 2015. Incidence based on documented International Classification of Diseases diagnosis of acute kidney injury and acute tubular necrosis during the intervention periods (3 periods of 6 months each: January 1 to June 30 of 2015, 2016, and 2017) were compared to one preintervention period (January 1, 2014, to June 30, 2014). The sample consisted of 269 607 adult hospital discharges, among which there were 39 071 episodes based on laboratory estimates and 27 660 episodes of documented International Classification of Diseases diagnoses of acute kidney injury or acute tubular necrosis. Documented incidence improved significantly from the 2014 preintervention period (5.70%; 95% confidence interval: 5.52%-5.88%) to intervention periods in 2015 (9.89%; 95% confidence interval, 9.66%-10.12%; risk ratio = 1.73, P < .001), 2016 (12.76%; 95% confidence interval, 12.51%-13.01%; risk ratio = 2.24, P < .001), and 2017 (12.49%; 95% confidence interval, 12.24%-12.74%; risk ratio = 2.19, P < .001). A multifactorial intervention comprising daily laboratory alerting and education of physicians, nurses, and clinical documentation improvement specialists led to increased recognition and clinical documentation of acute kidney injury.

Acute Kidney Injury Definition and Diagnosis: A Narrative Review

Acute kidney injury (AKI) is a complex syndrome characterized by a decrease in renal function and associated with numerous etiologies and pathophysiological mechanisms. It is a common diagnosis in hospitalized patients, with increasing incidence in recent decades, and associated with poorer short- and long-term outcomes and increased health care costs. Considering its impact on patient prognosis, research has focused on methods to assess patients at risk of developing AKI and diagnose subclinical AKI, as well as prevention and treatment strategies, for which an understanding of the epidemiology of AKI is crucial. In this review, we discuss the evolving definition and classification of AKI, and novel diagnostic methods.

Epidemiology, outcomes, and management of acute kidney injury in the vascular surgery patient

OBJECTIVE

Conventional clinical wisdom has often been nihilistic regarding the prevention and management of acute kidney injury (AKI), despite its being a frequent and morbid complication associated with both increased mortality and cost. Recent developments have shown that AKI is not inevitable and that changes in management of patients can reduce both the incidence and morbidity of perioperative AKI. The purpose of this narrative review was to review the epidemiology and outcomes of AKI in patients undergoing vascular surgery using current consensus definitions, to discuss some of the novel emerging risk stratification and prevention techniques relevant to the vascular surgery patient, and to describe a standardized perioperative pathway for the prevention of AKI after vascular surgery.

METHODS

We performed a critical review of the literature on AKI in the vascular surgery patient using the PubMed and MEDLINE databases and Google Scholar through September 2017 using web-based search engines. We also searched the guidelines and publications available online from the organizations Kidney Disease: Improving Global Outcomes and the Acute Dialysis Quality Initiative. The search terms used included acute kidney injury, AKI, epidemiology, outcomes, prevention, therapy, and treatment.

RESULTS

The reported epidemiology and outcomes associated with AKI have been evolving since the publication of consensus criteria that allow accurate identification of mild and moderate AKI. The incidence of AKI after major vascular surgery using current criteria is as high as 49%, although there are significant differences, depending on the type of procedure performed. Many tools have become available to assess and to stratify the risk for AKI and to use that information to prevent AKI in the surgical patient. We describe a standardized clinical assessment and management pathway for vascular surgery patients, incorporating current risk assessment and preventive strategies to prevent AKI and to decrease its complications. Patients without any risk factors can be managed in a perioperative fast-track pathway. Those patients with positive risk factors are tested for kidney stress using the urinary biomarker TIMP-2•IGFBP7, and care is then stratified according to the result. Management follows current Kidney Disease: Improving Global Outcomes guidelines.

CONCLUSIONS

AKI is a common postoperative complication among vascular surgery patients and has a significant impact on morbidity, mortality, and cost. Preoperative risk assessment and optimal perioperative management guided by that risk assessment can minimize the consequences associated with postoperative AKI. Adherence to a standardized perioperative pathway designed to reduce risk of AKI after major vascular surgery offers a promising clinical approach to mitigate the incidence and severity of this challenging clinical problem.

The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients

BACKGROUND

Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes.

METHODS AND FINDINGS

A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014-16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981-1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858-0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560-0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation.

CONCLUSIONS

In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness.

TRIAL REGISTRATION

Clinicaltrials.org NCT03047382.

Association Between Early Postoperative Acetaminophen Exposure and Acute Kidney Injury in Pediatric Patients Undergoing Cardiac Surgery

IMPORTANCE

Acute kidney injury (AKI) is a common and serious complication for pediatric cardiac surgery patients associated with increased morbidity, mortality, and length of stay. Current strategies focus on risk reduction and early identification because there are no known preventive or therapeutic agents. Cardiac surgery and cardiopulmonary bypass lyse erythrocytes, releasing free hemoglobin and contributing to oxidative injury. Acetaminophen may prevent AKI by reducing the oxidation state of free hemoglobin.

OBJECTIVE

To test the hypothesis that early postoperative acetaminophen exposure is associated with reduced risk of AKI in pediatric patients undergoing cardiac surgery.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective cohort study, the setting was 2 tertiary referral children's hospitals. The primary and validation cohorts included children older than 28 days admitted for cardiac surgery between July 1, 2008, and June 1, 2016. Exclusion criteria were postoperative extracorporeal membrane oxygenation and inadequate serum creatinine measurements to determine AKI status.

EXPOSURES

Acetaminophen exposure in the first 48 postoperative hours.

MAIN OUTCOMES AND MEASURES

Acute kidney injury based on Kidney Disease: Improving Global Outcomes serum creatinine criteria (increase by ≥0.3 mg/dL from baseline or at least 1.5-fold more than the baseline [to convert to micromoles per liter, multiply by 88.4]) in the first postoperative week.

RESULTS

The primary cohort (n = 666) had a median age of 6.5 (interquartile range [IQR], 3.9-44.7) months, and 341 (51.2%) had AKI. In unadjusted analyses, those with AKI had lower median acetaminophen doses than those without AKI (47 [IQR, 16-88] vs 78 [IQR, 43-104] mg/kg, P < .001). In logistic regression analysis adjusting for age, cardiopulmonary bypass time, red blood cell distribution width, postoperative hypotension, nephrotoxin exposure, and Risk Adjustment for Congenital Heart Surgery score, acetaminophen exposure was protective against postoperative AKI (odds ratio, 0.86 [95% CI, 0.82-0.90] per each additional 10 mg/kg). Findings were replicated in the validation cohort (n = 333), who had a median age of 14.1 (IQR, 3.9-158.2) months, and 162 (48.6%) had AKI. Acetaminophen doses were 60 (95% CI, 40-87) mg/kg in those with AKI vs 70 (95% CI, 45-94) mg/kg in those without AKI (P = .03), with an adjusted odds ratio of 0.91 (95% CI, 0.84-0.99) for each additional 10 mg/kg.

CONCLUSIONS AND RELEVANCE

These results indicate that early postoperative acetaminophen exposure may be associated with a lower rate of AKI in pediatric patients who undergo cardiac surgery. Further analysis to validate these findings, potentially through a prospective, randomized trial, may establish acetaminophen as a preventive agent for AKI.

Identification of Patients Expected to Benefit from Electronic Alerts for Acute Kidney Injury

BACKGROUND AND OBJECTIVES

Electronic alerts for heterogenous conditions such as AKI may not provide benefit for all eligible patients and can lead to alert fatigue, suggesting that personalized alert targeting may be useful. Uplift-based alert targeting may be superior to purely prognostic-targeting of interventions because uplift models assess marginal treatment effect rather than likelihood of outcome.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

This is a secondary analysis of a clinical trial of 2278 adult patients with AKI randomized to an automated, electronic alert system versus usual care. We used three uplift algorithms and one purely prognostic algorithm, trained in 70% of the data, and evaluated the effect of targeting alerts to patients with higher scores in the held-out 30% of the data. The performance of the targeting strategy was assessed as the interaction between the model prediction of likelihood to benefit from alerts and randomization status. The outcome of interest was maximum relative change in creatinine from the time of randomization to 3 days after randomization.

RESULTS

The three uplift score algorithms all gave rise to a significant interaction term, suggesting that a strategy of targeting individuals with higher uplift scores would lead to a beneficial effect of AKI alerting, in contrast to the null effect seen in the overall study. The prognostic model did not successfully stratify patients with regards to benefit of the intervention. Among individuals in the high uplift group, alerting was associated with a median reduction in change in creatinine of -5.3% (P=0.03). In the low uplift group, alerting was associated with a median increase in change in creatinine of +5.3% (P=0.005). Older individuals, women, and those with a lower randomization creatinine were more likely to receive high uplift scores, suggesting that alerts may benefit those with more slowly developing AKI.

CONCLUSIONS

Uplift modeling, which accounts for treatment effect, can successfully target electronic alerts for AKI to those most likely to benefit, whereas purely prognostic targeting cannot.

Value of electronic alerts for acute kidney injury in high-risk wards: a pilot randomized controlled trial

PURPOSE

To investigate the application value of "electronic alerts" ("e-alerts") for acute kidney injury (AKI) among high-risk wards of hospitals.

METHODS

A prospective, randomized, controlled study was conducted. We developed an e-alert system for AKI and ran the system in intensive care units and divisions focusing on cardiovascular disease. The e-alert system diagnosed AKI automatically based on serum creatinine levels. Patients were assigned randomly to an e-alert group (467 patients) or non-e-alert group (408 patients). Only the e-alert group could receive pop-up messages.

RESULTS

The sensitivity, specificity, Youden Index and accuracy of the AKI e-alert system were 99.8, 97.7, 97.5 and 98.1%, respectively. The prevalence of the diagnosis for AKI and expanded-AKI (AKI or multiple-organ failure) in the e-alert group was higher than that in the non-e-alert group (AKI 7.9 and 2.7%, P = 0.001; expanded-AKI 16.3 and 6.1%, P < 0.001). The prevalence of nephrology consultation in the e-alert group was higher than that in the non-e-alert group (9.0 and 3.7%, P = 0.001). There was no significant difference in the prevalence dialysis, rehabilitation of renal function or death in the two groups.

CONCLUSION

The e-alert system described here was a reliable tool to make an accurate diagnosis of AKI.

Acute Kidney Injury in Children

Acute kidney injury (AKI) has become one of the more common complications seen among hospitalized children. The development of a consensus definition has helped refine the epidemiology of pediatric AKI, and we now have a far better understanding of its incidence, risk factors, and outcomes. Strategies for diagnosing AKI have extended beyond serum creatinine, and the most current data underscore the diagnostic importance of oliguria as well as introduce the concept of urinary biomarkers of kidney injury. As AKI has become more widespread, we have seen that it is associated with a number of adverse consequences including longer lengths of stay and greater mortality. Though effective treatments do not currently exist for AKI once it develops, we hope that the diagnostic and definitional strides seen recently translate to the testing and development of more effective interventions.

Association between e-alert implementation for detection of acute kidney injury and outcomes: a systematic review

Background

Electronic alerts (e-alerts) for acute kidney injury (AKI) in hospitalized patients are increasingly being implemented; however, their impact on outcomes remains uncertain.

Methods

We performed a systematic review. Electronic databases and grey literature were searched for original studies published between 1990 and 2016. Randomized, quasi-randomized, observational and before-and-after studies that included hospitalized patients, implemented e-alerts for AKI and described their impact on one of care processes, patient-centred outcomes or resource utilization measures were included.

Results

Our search yielded six studies ( n  = 10 165 patients). E-alerts were generally automated, triggered through electronic health records and not linked to clinical decision support. In pooled analysis, e-alerts did not improve mortality [odds ratio (OR) 1.05; 95% confidence intervals (CI), 0.84-1.31; n  = 3 studies; n  = 3425 patients; I 2  =   0%] or reduce renal replacement therapy (RRT) use (OR 1.20; 95% CI, 0.91-1.57; n  = 2 studies; n  = 3236 patients; I 2  =   0%). Isolated studies reported improvements in selected care processes. Pooled analysis found no significant differences in prescribed fluid therapy.

Conclusions

In the available studies, e-alerts for AKI do not improve survival or reduce RRT utilization. The impact of e-alerts on processes of care was variable. Additional research is needed to understand those aspects of e-alerts that are most likely to improve care processes and outcomes.

Improvement of drug prescribing in acute kidney injury with a nephrotoxic drug alert system

Objective

Electronic alert systems have shown their capacity for improving the detection of acute kidney injury (AKI). The aim of this study was to design and implement a clinical decision support system (CDSS) for improving drug selection and reducing nephrotoxic drug use in patients with AKI.

Methods

The study was designed as an intervention study comparing a pre and post cohort of patients admitted during April 2014 and April 2015, respectively (phase I and phase II). The intervention was a CDSS which provided kidney function and nephrotoxic drug information. Furthermore, an interruptive alert was designed to detect patients suffering an AKI event while taking a nephrotoxic drug and to see if the dose was then reduced or the drug was discontinued by the physicians.

Results

One-third of the inpatients were included in the analysis because they met the inclusion criteria (1004 and 1002 patients in phases I and II, respectively). 735 and 761 of them received at least one nephrotoxic alert (73% vs 76%; p=0.763). 65 and 88 patients suffered AKI during admission (6.5% vs 8.8%; p=0.051). In phase I, patients received 384 nephrotoxic alerts (55%) with 78 (20%) of them provoking a change or discontinuation of the nephrotoxic drug. In phase II this value increased to 154 out of 526 (29%) after implementation of the CDSS (p<0.01).

Conclusions

A CDSS with interruptive alerts that inform of the development of AKI in real time in patients with nephrotoxic drug prescription has a positive impact on the judicious use of these drugs.

Electronic health record-based predictive models for acute kidney injury screening in pediatric inpatients

BackgroundAcute kidney injury (AKI) is common in pediatric inpatients and is associated with increased morbidity, mortality, and length of stay. Its early identification can reduce severity.MethodsTo create and validate an electronic health record (EHR)-based AKI screening tool, we generated temporally distinct development and validation cohorts using retrospective data from our tertiary care children's hospital, including children aged 28 days through 21 years with sufficient serum creatinine measurements to determine AKI status. AKI was defined as 1.5-fold or 0.3 mg/dl increase in serum creatinine. Age, medication exposures, platelet count, red blood cell distribution width, serum phosphorus, serum transaminases, hypotension (ICU only), and pH (ICU only) were included in AKI risk prediction models.ResultsFor ICU patients, 791/1,332 (59%) of the development cohort and 470/866 (54%) of the validation cohort had AKI. In external validation, the ICU prediction model had a c-statistic=0.74 (95% confidence interval 0.71-0.77). For non-ICU patients, 722/2,337 (31%) of the development cohort and 469/1,474 (32%) of the validation cohort had AKI, and the prediction model had a c-statistic=0.69 (95% confidence interval 0.66-0.72).ConclusionsAKI screening can be performed using EHR data. The AKI screening tool can be incorporated into EHR systems to identify high-risk patients without serum creatinine data, enabling targeted laboratory testing, early AKI identification, and modification of care.

Impact of e-alert systems on the care of patients with acute kidney injury

With the recent advancement in electronic health record systems and meaningful use of information technology incentive programs (i.e., the American Recovery and Reinvestment Act, the Health Information Technology for Economic and Clinical Health Act, and the Centers for Medicare & Medicaid Services), interest in clinical decision support systems has risen. These systems have been used to examine a variety of different syndromes with variable reported effects. In recent years, electronic alerts (e-alerts) have been implemented at various institutions to decrease the morbidity associated with acute kidney injury (AKI). AKI is common, accounting for 1 in 7 hospital admissions, and is associated with increased length of hospital stay and mortality. AKI is often underrecognized, causing delayed intervention. The use of e-alerts may result in earlier recognition and intervention, as well as decreased morbidity and mortality. This must be balanced with the possibility of increased resource utilization that e-alerts may cause. Before widespread implementation, the ethical and legal consequences of not following e-alert recommendations must be established, and the optimal algorithm for AKI e-alert detection must be determined.

Continuous Renal Replacement Therapy: Forty-year Anniversary

In 1977 Peter Kramer performed the first CAVH (continuous arteriovenous hemofiltration) treatment in Gottingen, Germany. CAVH soon became a reliable alternative to hemo- or peritoneal dialysis in critically ill patients. The limitations of CAVH spurred new research and the discovery of new treatments such as CVVH and CVVHD (continuous veno-venous hemofiltration and continuous veno-venous hemodialysis). The alliance with industry led to development of new specialized equipment with improved accuracy and performance in delivering continuous renal replacement therapies (CRRTs). Machines and filters have progressively undergone a series of technological steps, reaching a high level of sophistication. The evolution of technology has continued, leading to the development and clinical application of new membranes, new techniques and new treatment modalities. With the progress of technology, the entire field of critical care nephrology moved forward, expanding the areas of application of extracorporeal therapies to cardiac, liver and pulmonary support. A great deal of research made extracorporeal therapies an interesting option for the treatment of sepsis and intoxication and the additional use of sorbents was explored. With the progress in understanding the pathophysiology of acute kidney injury (AKI), new guidelines were developed, driving indications, modalities of prescription, monitoring techniques and quality assurance programs. Information technology and precision medicine have recently contributed to further evolution of CRRT, with the possibility of collecting data in large databases and evaluating policies and practice patterns. This is likely to ultimately result in improved patient care. CRRTs are 40 years old today, but they are still young and full of potential for further evolution.

Study of the uses of Information and Communication Technologies by Pain Treatment Unit Physicians

Adequate use of Information and Communication Technologies (ICTs) in health has been shown to save the patient and caregiver time, improve access to the health system, improve diagnosis and control of disease or treatment. All this results in cost savings, and more importantly, they help improve the quality of service and the lives of patients. The purpose of this study is to analyse the differences in the uses of this ICTs between those physicians that belong to Pain Treatment Units (PU) and other physicians that work in pain not linked to these PUs. An online survey, generated by Netquest online survey tool, was sent to both groups of professionals and the data collected was statistical analysed through a logistic regression methodology which is the Logit binomial model. Our results show that those physicians that belong to PUs use ICTs more frequently and consider it more relevant to their clinical practice.

Leveraging Big Data and Electronic Health Records to Enhance Novel Approaches to Acute Kidney Injury Research and Care

While acute kidney injury (AKI) has been poorly defined historically, a decade of effort has culminated in a standardized, consensus definition. In parallel, electronic health records (EHRs) have been adopted with greater regularity, clinical informatics approaches have been refined, and the field of EHR-enabled care improvement and research has burgeoned. Although both fields have matured in isolation, uniting the 2 has the capacity to redefine AKI-related care and research. This article describes how the application of a consistent AKI definition to the EHR dataset can accurately and rapidly diagnose and identify AKI events. Furthermore, this electronic, automated diagnostic strategy creates the opportunity to develop predictive approaches, optimize AKI alerts, and trace AKI events across institutions, care platforms, and administrative datasets.

Biomarkers for the Early Detection and Prognosis of Acute Kidney Injury

AKI is an increasingly common disorder that is strongly linked to short- and long-term morbidity and mortality. Despite a growing heterogeneity in its causes, providing a timely and certain diagnosis of AKI remains challenging. In this review, we summarize the evolution of AKI biomarker studies over the past few years, focusing on two major areas of investigation: the early detection and prognosis of AKI. We highlight some of the lessons learned in conducting AKI biomarker studies, including ongoing attempts to address the limitations of creatinine as a reference standard and the recent shift toward evaluating the prognostic potential of these markers. Lastly, we suggest current gaps in knowledge and barriers that may be hindering their incorporation into care and a full ascertainment of their value.

Clinical decision support for drug related events: Moving towards better prevention

Clinical decision support (CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors (ME) and adverse drug events (ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.

Identification of Major Adverse Kidney Events Within the Electronic Health Record

Acute kidney injury is common among critically ill adults and is associated with increased mortality and morbidity. The Major Adverse Kidney Events by 30 days (MAKE30) composite of death, new renal replacement therapy, or persistent renal dysfunction is recommended as a patient-centered outcome for pragmatic trials involving acute kidney injury. Accurate electronic detection of the MAKE30 endpoint using data within the electronic health record (EHR) could facilitate the use of the EHR in large-scale kidney injury research. In an observational study using prospectively collected data from 200 admissions to a single medical intensive care unit, we tested the performance of electronically-extracted data in identifying the MAKE30 composite compared to the reference standard of two-physician manual chart review. The incidence of MAKE30 on manual-review was 16 %, which included 8.5 % for in-hospital mortality, 3.5 % for new renal replacement therapy, and 8.5 % for persistent renal dysfunction. There was strong agreement between the electronic and manual assessment of MAKE30 (98.5 % agreement [95 % CI 96.5-100.0 %]; kappa 0.95 [95 % CI 0.87-1.00]; P < 0.001), with only three patients misclassified by electronic assessment. Performance of the electronic MAKE30 assessment was similar among patients with and without CKD and with and without a measured serum creatinine in the 12 months prior to hospital admission. In summary, accurately identifying the MAKE30 composite outcome using EHR data collected as a part of routine care appears feasible.

Impact of e-alert for detection of acute kidney injury on processes of care and outcomes: protocol for a systematic review and meta-analysis

INTRODUCTION

Acute kidney injury (AKI) is a common complication in hospitalised patients. It imposes significant risk for major morbidity and mortality. Moreover, patients suffering an episode of AKI consume considerable health resources. Recently, a number of studies have evaluated the implementation of automated electronic alerts (e-alerts) configured from electronic medical records (EMR) and clinical information systems (CIS) to warn healthcare providers of early or impending AKI in hospitalised patients. The impact of e-alerts on care processes, patient outcomes and health resource use, however, remains uncertain.

METHODS AND ANALYSIS

We will perform a systematic review to describe and appraise e-alerts for AKI, and evaluate their impact on processes of care, clinical outcomes and health services use. In consultation with a research librarian, a search strategy will be developed and electronic databases (ie, MEDLINE, EMBASE, CINAHL, Cochrane Library and Inspec via Engineering Village) searched. Selected grey literature sources will also be searched. Search themes will focus on e-alerts and AKI. Citation screening, selection, quality assessment and data abstraction will be performed in duplicate. The primary analysis will be narrative; however, where feasible, pooled analysis will be performed. Each e-alert will be described according to trigger, type of alert, target recipient and degree of intrusiveness. Pooled effect estimates will be described, where applicable.

ETHICS AND DISSEMINATION

Our systematic review will synthesise the literature on the value of e-alerts to detect AKI, and their impact on processes, patient-centred outcomes and resource use, and also identify key knowledge gaps and barriers to implementation. This is a fundamental step in a broader research programme aimed to understand the ideal structure of e-alerts, target population and methods for implementation, to derive benefit. Research ethics approval is not required for this review.

SYSTEMATIC REVIEW REGISTRATION NUMBER

CRD42016033033.