Impact of electronic-alerting of acute kidney injury: workgroup statements from the 15(th) ADQI Consensus Conference

Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan

Purpose

To address the contentious data sharing across hospitals, this study adopted a novel approach, federated learning (FL), to establish an aggregate model for acute kidney injury (AKI) prediction in critically ill patients in Taiwan.

Methods

This study used data from the Critical Care Database of Taichung Veterans General Hospital (TCVGH) from 2015 to 2020 and electrical medical records of the intensive care units (ICUs) between 2018 and 2020 of four referral centers in different areas across Taiwan. AKI prediction models were trained and validated thereupon. An FL-based prediction model across hospitals was then established.

Results

The study included 16,732 ICU admissions from the TCVGH and 38,424 ICU admissions from the other four hospitals. The complete model with 60 features and the parsimonious model with 21 features demonstrated comparable accuracies using extreme gradient boosting, neural network (NN), and random forest, with an area under the receiver-operating characteristic (AUROC) curve of approximately 0.90. The Shapley Additive Explanations plot demonstrated that the selected features were the key clinical components of AKI for critically ill patients. The AUROC curve of the established parsimonious model for external validation at the four hospitals ranged from 0.760 to 0.865. NN-based FL slightly improved the model performance at the four centers.

Conclusion

A reliable prediction model for AKI in ICU patients was developed with a lead time of 24 h, and it performed better when the novel FL platform across hospitals was implemented.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-023-00248-5.

Design, validation and implementation of an automated e-alert for acute kidney injury: 6-month pilot study shows increased awareness

BACKGROUND

Acute kidney injury (AKI) is defined as a sudden episode of kidney failure but is known to be under-recognized by healthcare professionals. The Kidney Disease Improving Global Outcome (KDIGO) guidelines have formulated criteria to facilitate AKI diagnosis by comparing changes in plasma creatinine measurements (PCr). To improve AKI awareness, we implemented these criteria as an electronic alert (e-alert), in our electronic health record (EHR) system.

METHODS

For every new PCr measurement measured in the University Medical Center Utrecht that triggered the e-alert, we provided the physician with actionable insights in the form of a memo, to improve or stabilize kidney function. Since e-alerts qualify for software as a medical device (SaMD), we designed, implemented and validated the e-alert according to the European Union In Vitro Diagnostic Regulation (IVDR).

RESULTS

We evaluated the impact of the e-alert using pilot data six months before and after implementation. 2,053 e-alerts of 866 patients were triggered in the before implementation, and 1,970 e-alerts of 853 patients were triggered after implementation. We found improvements in AKI awareness as measured by (1) 2 days PCr follow up (56.6-65.8%, p-value: 0.003), and (2) stop of nephrotoxic medication within 7 days of the e-alert (59.2-63.2%, p-value: 0.002).

CONCLUSION

Here, we describe the design and implementation of the e-alert in line with the IVDR, leveraging a multi-disciplinary team consisting of physicians, clinical chemists, data managers and data scientists, and share our firsts results that indicate an improved awareness among treating physicians.

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.

Impact of an Electronic Alert in Combination with a Care Bundle on the Outcomes of Acute Kidney Injury

Early diagnosis is essential for the appropriate management of acute kidney injury (AKI). We evaluated the impact of an electronic AKI alert together with a care bundle on the progression and mortality of AKI. This was a single-center prospective study that included AKI patients aged ≥ 18 years, whereas those in palliative care, nephrology, and transplantation departments were excluded. An AKI alert was issued in electronic medical records and a care bundle was suggested. A series of classes were administered to the multidisciplinary teams by nephrologists, and a clinical pharmacist audited prescriptions. Patients were categorized into pre-alert and post-alert groups. The baseline characteristics were comparable between the pre-alert (n = 1613) and post-alert (n = 1561) groups. The 30-day mortality rate was 33.6% in the entire cohort and was lower in the post-alert group (30.5% vs. 36.7%; p < 0.001). Age, pulmonary disease, malignancy, and ICU admission were associated with an increase in 30-day mortality. The electronic AKI alert together with a care bundle and a multidisciplinary education program was associated with a reduction in 30-day mortality in patients with AKI.

Opportunities in digital health and electronic health records for acute kidney injury care

PURPOSE OF REVIEW

The field of digital health is evolving rapidly with applications relevant to the prediction, detection and management of acute kidney injury (AKI). This review will summarize recent publications in these areas.

RECENT FINDINGS

Machine learning (ML) approaches have been applied predominantly for AKI prediction, but also to identify patients with AKI at higher risk of adverse outcomes, and to discriminate different subgroups (subphenotypes) of AKI. There have been multiple publications in this area, but a smaller number of ML models have robust external validation or the ability to run in real-time in clinical systems. Recent studies of AKI alerting systems and clinical decision support systems continue to demonstrate variable results, which is likely to result from differences in local context and implementation strategies. In the design of AKI alerting systems, choice of baseline creatinine has a strong effect on performance of AKI detection algorithms.

SUMMARY

Further research is required to overcome barriers to the validation and implementation of ML models for AKI care. Simpler electronic systems within the electronic medical record can lead to improved care in some but not all settings, and careful consideration of local context and implementation strategy is recommended.

Update on Pediatric Acute Kidney Injury

Acute kidney injury (AKI) is common in children and is associated with significant morbidity and mortality. In the last decade our understanding of AKI has improved significantly, and it is now considered a systemic disorder that affects other organs including heart, lung, and brain. In spite of its limitations, serum creatinine remains the mainstay in the diagnosis of AKI. However, newer approaches such as urinary biomarkers, furosemide stress test, and clinical decision support are being increasingly used and have the potential to improve the accuracy and timeliness of AKI diagnosis.

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.

Nephrotoxins and acute kidney injury - The consensus of the Taiwan acute kidney injury Task Force

The Taiwan Acute Kidney Injury (AKI) Task Force conducted a review of data and developed a consensus regarding nephrotoxins and AKI. This consensus covers: (1) contrast-associated AKI; (2) drug-induced nephrotoxicity; (3) prevention of drug-associated AKI; (4) follow up after AKI; (5) re-initiation of medication after AKI. Strategies for the avoidance of contrast media related AKI, including peri-procedural hydration, sodium bicarbonate solutions, oral N-acetylcysteine, and iso-osmolar/low-osmolar non-ionic iodinated contrast media have been recommended, given the respective evidence levels. Regarding anticoagulants, both warfarin and new oral anticoagulants have potential nephrotoxicity, and dosage should be reduced if renal pathology exam proves renal injury. Recommended strategies to prevent drug related AKI have included assessment of 5R/(6R) reactions - risk, recognition, response, renal support, rehabilitation and (research), use of AKI alert system and computerized decision support. In terms of antibiotics-associated AKI, avoiding concomitant administration of vancomycin and piperacillin-tazobactam, monitoring vancomycin trough level, switching from vancomycin to teicoplanin in high-risk patients, and replacing conventional amphotericin B with lipid-based amphotericin B have been shown to reduce drug related AKI. With respect to non-steroidal anti-inflammatory drug associated AKI, it is recommended to use these drugs cautiously in the elderly and in patients receiving renin-angiotensin-aldosterone system inhibitors/diuretics triple combinations.

The use of diagnostic tools for pediatric AKI: applying the current evidence to the bedside

Given the known deleterious consequences of acute kidney injury (AKI), exciting recent research efforts have focused on developing strategies for the earlier recognition of AKI in the pediatric population. Recognizing the limitations of serum creatinine, investigators have focused on the study of novel biomarkers and practical bedside tools for identifying patients at risk for AKI prior to a rise in serum creatinine. In PubMed, there are presently over 30 original research papers exploring the use of pediatric AKI risk prediction tools in just the last 2 years. The following review highlights the most recent advances in the literature regarding opportunities to refine our ability to detect AKI early. Importantly, this review discusses how prediction tools including novel urine and serum biomarkers, practical risk stratification tests, renal functional reserve, and electronic medical record alerts may ultimately be applied to routine clinical practice.

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.

Impact of AKI care bundles on kidney and patient outcomes in hospitalized patients: a systematic review and meta-analysis

Background

A bundle of preventive measures can be taken to avoid acute kidney injury (AKI) or progression of AKI. We performed a systematic review and meta-analysis to evaluate the compliance to AKI care bundles in hospitalized patients and its impact on kidney and patient outcomes.

Methods

Randomized controlled trials, observational and interventional studies were included. Studied outcomes were care bundle compliance, occurrence of AKI and moderate-severe AKI, use of kidney replacement therapy (KRT), kidney recovery, mortality (ICU, in-hospital and 30-day) and length-of-stay (ICU, hospital). The search engines PubMed, Embase and Google Scholar were used (January 1, 2012 - June 30, 2021). Meta-analysis was performed with the Mantel Haenszel test (risk ratio) and inverse variance (mean difference). Bias was assessed by the Cochrane risk of bias tool (RCT) and the NIH study quality tool (non-RCT).

Results

We included 23 papers of which 13 were used for quantitative analysis (4 RCT and 9 non-randomized studies with 25,776 patients and 30,276 AKI episodes). Six were performed in ICU setting. The number of trials pooled per outcome was low. There was a high variability in care bundle compliance (8 to 100%). Moderate-severe AKI was less frequent after bundle implementation [RR 0.78, 95%CI 0.62–0.97]. AKI occurrence and KRT use did not differ between the groups [resp RR 0.90, 95%CI 0.76–1.05; RR 0.67, 95%CI 0.38–1.19]. In-hospital and 30-day mortality was lower in AKI patients exposed to a care bundle [resp RR 0.81, 95%CI 0.73–0.90, RR 0.95 95%CI 0.90–0.99]; this could not be confirmed by randomized trials. Hospital length-of-stay was similar in both groups [MD -0.65, 95%CI -1.40,0.09].

Conclusion

This systematic review and meta-analysis shows that implementation of AKI care bundles in hospitalized patients reduces moderate-severe AKI. This result is mainly driven by studies performed in ICU setting. Lack of data and heterogeneity in study design impede drawing firm conclusions about patient outcomes. Moreover, compliance to AKI care bundles in hospitalized patients is highly variable. Additional research in targeted patient groups at risk for moderate-severe AKI with correct and complete implementation of a feasible, well-tailored AKI care bundle is warranted. (CRD42020207523).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02534-4.

Effect of clinical decision support systems on clinical outcome for acute kidney injury: a systematic review and meta-analysis

Background

Clinical decision support systems including both electronic alerts and care bundles have been developed for hospitalized patients with acute kidney injury.

Methods

Electronic databases were searched for randomized, before-after and cohort studies that implemented a clinical decision support system for hospitalized patients with acute kidney injury between 1990 and 2019. The studies must describe their impact on care processes, patient-related outcomes, or hospital length of stay. The clinical decision support system included both electronic alerts and care bundles.

Results

We identified seven studies involving 32,846 participants. Clinical decision support system implementation significantly reduced mortality (OR 0.86; 95 % CI, 0.75–0.99; p = 0.040, I² = 65.3 %; n = 5 studies; N = 30,791 participants) and increased the proportion of acute kidney injury recognition (OR 3.12; 95 % CI, 2.37–4.10; p < 0.001, I² = 77.1 %; n = 2 studies; N = 25,121 participants), and investigations (OR 3.07; 95 % CI, 2.91–3.24; p < 0.001, I² = 0.0 %; n = 2 studies; N = 25,121 participants).

Conclusions

Nonrandomized controlled trials of clinical decision support systems for acute kidney injury have yielded evidence of improved patient-centered outcomes and care processes. This review is limited by the low number of randomized trials and the relatively short follow-up period.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02459-y.

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

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

Impact of integrated clinical decision support systems in the management of pediatric acute kidney injury: a pilot study

BACKGROUND

Acute kidney injury (AKI) is common but not often recognized. Early recognition and management may improve patient outcomes.

METHODS

This is a prospective, nonrandomized study of clinical decision support (CDS) system [combining electronic alert and standardized care pathway (SCP)] to evaluate AKI detection and progression in hospitalized children. The study was done in three phases: pre-, intervention (CDS) and post. During CDS, text-page with AKI stage and link to SCP was sent to patient's contact provider at diagnosis of AKI using creatinine. The SCP provided guidelines on AKI management [AEIOU: Assess cause of AKI, Evaluate drug doses, Intake-Output charting, Optimize volume status, Urine dipstick].

RESULTS

In all, 239 episodes of AKI in 225 patients (97 females, 43.1%) were analyzed. Proportion of patients with decrease in the stage of AKI after onset was 71.4% for CDS vs. 64.4% for pre- and 55% for post-CDS phases (p = 0.3). Documentation of AKI was higher during CDS (74.3% CDS vs. 47.5% pre- and 57.5% post-, p < 0.001). Significantly greater proportion of patients had nephrotoxic medications adjusted, or fluid plan changed during CDS. Patients from CDS phase had higher eGFR at discharge and at follow-up.

CONCLUSIONS

AKI remains under-recognized. CDS (electronic alerts and SCP) improve recognition and allow early intervention. This may improve long-term outcomes, but larger studies are needed.

IMPACT

Acute kidney injury can cause significant morbidity and mortality. It is under-recognized in children. Clinical decision support can be used to leverage existing data in the electronic health record to improve AKI recognition. This study demonstrates the use of a novel, electronic health record-linked, clinical decision support tool to improve the recognition of AKI and guideline-adherent clinical care.

Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial

OBJECTIVE

To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury.

DESIGN

Double blinded, multicenter, parallel, randomized controlled trial.

SETTING

Six hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers.

PARTICIPANTS

6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria.

INTERVENTIONS

An electronic health record based "pop-up" alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient's medical record.

MAIN OUTCOME MEASURES

A composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each hospital and frequency of various care practices for acute kidney injury.

RESULTS

6030 patients were randomized over 22 months. The primary outcome occurred in 653 (21.3%) of 3059 patients with an alert and in 622 (20.9%) of 2971 patients receiving usual care (relative risk 1.02, 95% confidence interval 0.93 to 1.13, P=0.67). Analysis by each hospital showed worse outcomes in the two non-teaching hospitals (n=765, 13%), where alerts were associated with a higher risk of the primary outcome (relative risk 1.49, 95% confidence interval 1.12 to 1.98, P=0.006). More deaths occurred at these centers (15.6% in the alert group v 8.6% in the usual care group, P=0.003). Certain acute kidney injury care practices were increased in the alert group but did not appear to mediate these outcomes.

CONCLUSIONS

Alerts did not reduce the risk of our primary outcome among patients in hospital with acute kidney injury. The heterogeneity of effect across clinical centers should lead to a re-evaluation of existing alerting systems for acute kidney injury.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02753751.

Artificial intelligence to guide management of acute kidney injury in the ICU: a narrative review

PURPOSE OF REVIEW

Acute kidney injury (AKI) frequently complicates hospital admission, especially in the ICU or after major surgery, and is associated with high morbidity and mortality. The risk of developing AKI depends on the presence of preexisting comorbidities and the cause of the current disease. Besides, many other parameters affect the kidney function, such as the state of other vital organs, the host response, and the initiated treatment. Advancements in the field of informatics have led to the opportunity to store and utilize the patient-related data to train and validate models to detect specific patterns and, as such, predict disease states or outcomes.

RECENT FINDINGS

Machine-learning techniques have also been applied to predict AKI, as well as the patients' outcomes related to their AKI, such as mortality or the need for kidney replacement therapy. Several models have recently been developed, but only a few of them have been validated in external cohorts.

SUMMARY

In this article, we provide an overview of the machine-learning prediction models for AKI and its outcomes in critically ill patients and individuals undergoing major surgery. We also discuss the pitfalls and the opportunities related to the implementation of these models in clinical practices.

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.

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.

AKI!Now Initiative: Recommendations for Awareness, Recognition, and Management of AKI

The American Society of Nephrology has established a new initiative, AKI!Now, with the goal of promoting excellence in the prevention and treatment of AKI by building a foundational program that transforms education and delivery of AKI care, aiming to reduce morbidity and associated mortality and to improve long-term outcomes. In this article, we describe our current efforts to improve early recognition and management involving inclusive interdisciplinary collaboration between providers, patients, and their families; discuss the ongoing need to change some of our current AKI paradigms and diagnostic methods; and provide specific recommendations to improve AKI recognition and care. In the hospital and the community, AKI is a common and increasingly frequent condition that generates risks of adverse events and high costs. Unfortunately, patients with AKI may frequently have received less than optimal quality of care. New classifications have facilitated understanding of AKI incidence and its impact on outcomes, but they are not always well aligned with AKI pathophysiology. Despite ongoing research efforts, treatments to promote or hasten kidney recovery remain ineffective. To avoid progression, the current approach to AKI emphasizes the promotion of early recognition and timely response. However, a lack of awareness of the importance of early recognition and treatment among health care team members and the heterogeneity of approaches within the health care teams assessing the patient remains a major challenge. Early identification is further complicated by differences in settings where AKI occurs (the community or the hospital), and by differences in patient populations and cultures between the intensive care unit and ward environments. To address these obstacles, we discuss the need to improve education at all levels of care and to generate specific guidance on AKI evaluation and management, including the development of a widely applicable education and an AKI management toolkit, engaging hospital administrators to incorporate AKI as a quality initiative, and raising awareness of AKI as a complication of other disease processes.

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.

[Treatment, clinical course, and cross-sectoral information transmission in patients with acute-on-chronic kidney injury]

BACKGROUND

Delayed diagnosis and undertherapy of acute-on-chronic kidney injury (AKI-on-CKD) may trigger multiple organ injury and worsen clinical outcome.

OBJECTIVES

This study focused on description of in-hospital care and cross-sectoral information transmission of patients with AKI-on-CKD including subgroup analyses (under surgical vs. non-surgical and nephrology vs. non-nephrology care).

MATERIALS AND METHODS

At a university clinic, we analysed clinical measures and documentation in patients with AKI-on-CKD. Cox regression was performed to identify independent risk factors for in-hospital-mortality and 180-day mortality.

RESULTS

In 38 (25.3%) of 150 patients, progressing AKI-on-CKD was found. Nineteen patients (12.7%) received acute dialysis. Thirty patients (20.0%) died in hospital. Systemic hypotension (n = 76, 50.7%) and nephrotoxins (n = 26, 17.3%), both considered as causes for AKI-on-CKD, were treated in 36.8 and 19.2%, respectively, of affected patients. Fluid balance was documented in one third of patients. Nephrology referral was requested in 38 (25.3%) of patients (median 24.0 h after AKI-on-CKD start). Acute renal complications (n = 74, 49.3%) were an independent risk factor for in-hospital mortality (ExpB 6.5, p = 0.022) or 180-day mortality (ExpB 3.3, p = 0.034). Rarely, outpatient physicians were informed about AKI-on-CKD (n = 42, 28.0%) or renal function follow-up was recommended (n = 14, 11.7% of surviving patients).

CONCLUSIONS

Care gaps in therapy and cross-sectoral information transmission in patients with AKI-on-CKD were identified.

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.

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.

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.

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.

Automated acute kidney injury alerts

Acute kidney injury (AKI) is one of the most common and probably one of the more consequential complications of critical illnesses. Recent information indicates that it is at least partially preventable; however, progress in its prevention, management, and treatment has been hindered by the scarcity of knowledge for effective interventions, inconsistencies in clinical practices, late identification of patients at risk for or with AKI, and limitations of access to best practices for prevention and management of AKI. Growing use of electronic health records has provided a platform for computer science to engage in data mining and processing, not only for early detection of AKI but also for the development of risk-stratification strategies and computer clinical decision-support (CDS) systems. Despite promising perspectives, the literature regarding the impact of AKI electronic alerts and CDS systems has been conflicting. Some studies have reported improvement in care processes and patient outcomes, whereas others have shown no effect on clinical outcomes and yet demonstrated an increase in the use of resources. These discrepancies are thought to be due to multiple factors that may be related to technology, human factors, modes of delivery of information to clinical providers, and level of expectations regarding the impact on patient outcomes. This review appraises the current body of knowledge and provides some outlines regarding research into and clinical aspects of CDS systems for AKI.

Computer decision support for acute kidney injury: current and future

PURPOSE OF REVIEW

Growing awareness regarding the impact of acute kidney injury (AKI) as a grave consequence of critical illnesses resulted in the expansion of the need for early detection and appropriate management strategies. Clinical decision support systems (CDSS) can generate information to improve the care of AKI patients by providing point-of-care accurate patient-specific information and recommendations. Our objective is to describe the characteristics of CDSS and review the current knowledge regarding the impact of CDSS on patients in the acute care settings, and specifically for AKI.

RECENT FINDINGS

Several recent systematic analyses showed the positive impact of CDSS on critically ill patients care processes. These studies also highlighted the scarcity of data regarding the effect of CDSS on the patient outcomes. In the field of AKI, there have been several reports to describe development and validation of homegrown CDSS and electronic alert systems. A large number of investigations showed the implementation of CDSS could improve the quality of AKI care; although, only in a very small subgroup of these studies patient outcomes improved.

SUMMARY

The heterogeneity of these studies in their size, design, and conduct has produced controversial findings; hence, this has left the field completely open for further investigations.

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.

Biomarkers for Early Detection of Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is common in hospitalized patients and is associated with increased morbidity, mortality, and cost. Currently, AKI is diagnosed after symptoms manifest; available diagnostic tests (e.g., serum creatinine, urine microscopy, urine output) have limited ability to identify subclinical AKI. Because of the lack of treatment strategies, AKI typically is managed with supportive measures. However, strategies exist that may prevent renal insults in critically ill patients; therefore, early recognition of AKI is crucial for minimizing damage propagation.

CONTENT

Experimental and clinical studies have identified biomarkers that may facilitate earlier recognition of AKI or even identify patients at risk of AKI. Such biomarkers might aid in earlier implementation of preventive strategies to slow disease progression and potentially improve outcomes. This review describes some of the most promising novel biomarkers of AKI, including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1), interleukin 18 (lL-18), liver-type fatty-acid-binding protein (L-FABP), insulin-like-growth-factor-binding protein 7 (IGFBP7), and tissue inhibitor of metalloproteinase 2 (TIMP-2).

SUMMARY

We discuss biomarker test characteristics, their strengths and weaknesses, and future directions of their clinical implementation.

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.

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.

Evaluation of Absolute Serum Creatinine Changes in Staging of Cirrhosis-Induced Acute Renal Injury and its Association with Long-term Outcomes

BACKGROUND/AIMS

To assess the prognostic accuracy of absolute serum creatinine (sCr) changes ('Delta-sCr') on the long-term outcomes in cirrhotic patients, and evaluate the performance of the 'Delta-sCr' approach to stage acute kidney injury (AKI), compared with the Kidney Disease Improving Global Outcomes (KDIGO) criteria.

METHODS

We conducted a retrospective analysis of 333 hospitalized patients. We classified AKI stages using two methods: 1) KDIGO AKI criteria; 2) 'Delta-sCr' system, defined by the difference between the baseline and the peak sCr value during the hospitalization. The end point was the hazard of 1-year death.

RESULTS

The prevalence of AKI in cirrhotic patients was 18.01% by the KDIGO criteria, and 25.22% by the 'Delta-sCr' system. On multivariable Cox hazard analysis, both of the two methods were independent predictive factors of death ('Delta-sCr' system: OR=2.911, p<0.001), (KDIGO criteria: OR=2.065, p<0.001). However, the 'Delta-sCr' system provided a modest improvement in classification over the KDIGO criteria with a net reclassification improvement (NRI) of 28.7% (p<0.001) and integrated discrimination improvement (IDI) of 7.5% (p=0.03). And the predictive value of the 'Delta-sCr' system could be significantly improved (p=0.006), when combined with age and MELD score.

CONCLUSION

The Delta-sCr is associated with the 1-year mortality. And the 'Delta-sCr' system may optimize the discrimination of risk prediction.

No increase in the incidence of acute kidney injury in a population-based annual temporal trends epidemiology study

Recent literature suggests an increase in the incidence of acute kidney injury (AKI). We evaluated population-based trends of AKI over the course of nine years, using a validated electronic health record tool to detect AKI. All adult residents (18 years of age and older) of Olmsted County, Minnesota (MN), admitted to the Mayo Clinic Hospital between 2006 and 2014 were included. The incidence rate of AKI was calculated and temporal trends in the annual AKI incident rates assessed. During the nine-year study period, 10,283, and 41,847 patients were admitted to the intensive care unit or general ward, with 1,740 and 2,811 developing AKI, respectively. The unadjusted incidence rates were 186 and 287 per 100,000 person years in 2006 and reached 179 and 317 per 100,000 person years in 2014. Following adjustment for age and sex, there was no significant change in the annual AKI incidence rate during the study period with a Relative Risk of 0.99 per year (95% confidence interval 0.97-1.01) for intensive care unit patients and 0.993 per year (0.98-1.01) for the general ward patients. Similar results were obtained when the ICD-9 codes or administrative data for dialysis-requiring AKI was utilized to determine incident cases. Thus, despite the current literature that suggests an epidemic of AKI, we found that after adjusting for age and sex the incidence of AKI in the general population remained relatively stable over the last decade.

The future of critical care: renal support in 2027

Since its inception four decades ago, both the clinical and technologic aspects of continuous renal replacement therapy (CRRT) have evolved substantially. Devices now specifically designed for critically ill patients with acute kidney injury are widely available and the clinical challenges associated with treating this complex patient population continue to be addressed. However, several important questions remain unanswered, leaving doubts in the minds of many clinicians about therapy prescription/delivery and patient management. Specifically, questions surrounding therapy dosing, timing of initiation and termination, fluid management, anticoagulation, drug dosing, and data analytics may lead to inconsistent delivery of CRRT and even reluctance to prescribe it. In this review, we discuss current limitations of CRRT and potential solutions over the next decade from both a patient management and a technology perspective. We also address the issue of sustainability for CRRT and related therapies beyond 2027 and raise several points for consideration.

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.

Electronic Alerts for Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) often takes a complicated course if diagnosed late and undertreated. Electronic alerts that provide an early warning of AKI are intended to support treating physicians in making the diagnosis of AKI and treating it appropriately. The available evidence on the effects of such alert systems is inconsistent.

METHODS

We employed the PRISMA recommendations for systematic literature reviews to identify relevant articles in the PubMed, Scopus, and Web of Science databases. All of the studies that were retrieved were independently assessed by two of the authors with respect to the methods of computer-assisted electronic alert systems and their effects on process indicators and clinical endpoints.

RESULTS

16 studies with a total of 32 842 patients were identified. 8.5% of admitted patients had community-acquired or hospital-acquired AKI, with an in-hospital mortality of 22.8%. Fifteen electronic alert systems were in use throughout the participating hospitals. In 13 of 15 studies, alarm activation was accompanied by concrete treatment recommendations. A randomized controlled trial in which no such recommendations were given did not reveal any benefit of the alert system for the patients. In controlled but non-randomized trials, however, the provision of concrete treatment recommendations when the alert was activated led to more frequent implementation of diagnostic or therapeutic measures, less loss of renal function, lower in-hospital mortality, and lower mortality after discharge compared to control groups without an electronic alert for AKI.

CONCLUSION

Non-randomized controlled trials of electronic alerts for AKI that were coupled with treatment recommendations have yielded evidence of improved care processes and treatment outcomes for patients with AKI. This review is limited by the low number of randomized trials and the wide variety of endpoints used in the studies that were evaluated.

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.