Electronic alerts and a care bundle for acute kidney injury-an Australian cohort study

Automated Electronic Alert for the Care and Outcomes of Adults With Acute Kidney Injury: A Randomized Clinical Trial

Importance

Despite the expansion of published electronic alerts for acute kidney injury (AKI), there are still concerns regarding their effect on the clinical outcomes of patients.

Objective

To evaluate the effect of the AKI alert combined with a care bundle on the care and clinical outcomes of patients with hospital-acquired AKI.

Design, Setting, and Participants

This single-center, double-blind, parallel-group randomized clinical trial was conducted in a tertiary teaching hospital in Nanjing, China, from August 1, 2019, to December 31, 2021. The inclusion criteria were inpatient adults aged 18 years or older with AKI, which was defined using the Kidney Disease: Improving Global Outcomes creatinine criteria. Participants were randomized 1:1 to either the alert group or the usual care group, which were stratified by medical vs surgical ward and by intensive care unit (ICU) vs non-ICU setting. Analyses were conducted on the modified intention-to-treat population.

Interventions

A programmatic AKI alert system generated randomization automatically and sent messages to the mobile telephones of clinicians (alert group) or did not send messages (usual care group). A care bundle accompanied the AKI alert and consisted of general, nonindividualized, and nonmandatory AKI management measures.

Main Outcomes and Measures

The primary outcome was maximum change in estimated glomerular filtration rate (eGFR) within 7 days after randomization. Secondary patient-centered outcomes included death, dialysis, AKI progression, and AKI recovery. Care-centered outcomes included diagnostic and therapeutic interventions for AKI.

Results

A total of 2208 patients (median [IQR] age, 65 [54-72] years; 1560 males [70.7%]) were randomized to the alert group (n = 1123) or the usual care group (n = 1085) and analyzed. Within 7 days of randomization, median (IQR) maximum absolute changes in eGFR were 3.7 (-6.4 to 19.3) mL/min/1.73 m2 in the alert group and 2.9 (-9.2 to 16.9) mL/min/1.73 m2 in the usual care group (P = .24). This result was robust in all subgroups in an exploratory analysis. For care-centered outcomes, patients in the alert group had more intravenous fluids (927 [82.6%] vs 670 [61.8%]; P < .001), less exposure to nonsteroidal anti-inflammatory drugs (56 [5.0%] vs 119 [11.0%]; P < .001), and more AKI documentation at discharge (560 [49.9%] vs 296 [27.3%]; P < .001) than patients in the usual care group. No differences were observed in patient-centered secondary outcomes between the 2 groups.

Conclusions and Relevance

Results of this randomized clinical trial showed that the electronic AKI alert did not improve kidney function or other patient-centered outcomes but changed patient care behaviors. The findings warrant the use of a combination of high-quality interventions and AKI alert in future clinical practice.

Trial Registration

ClinicalTrials.gov Identifier: NCT03736304.

Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup

Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and management of AKI has advanced over the past decades, its incidence and related morbidity, mortality and health care burden remain overwhelming. The rapid growth of digital technologies has provided a new platform to improve patient care, and reports show demonstrable benefits in care processes and, in some instances, in patient outcomes. However, despite great progress, the potential benefits of using digital technology to manage AKI has not yet been fully explored or implemented in clinical practice. Digital health studies in AKI have shown variable evidence of benefits, and the digital divide means that access to digital technologies is not equitable. Upstream research and development costs, limited stakeholder participation and acceptance, and poor scalability of digital health solutions have hindered their widespread implementation and use. Here, we provide recommendations from the Acute Disease Quality Initiative consensus meeting, which involved experts in adult and paediatric nephrology, critical care, pharmacy and data science, at which the use of digital health for risk prediction, prevention, identification and management of AKI and its consequences was discussed.

Improvement of composite kidney outcomes by AKI care bundles: a systematic review and meta-analysis

INTRODUCTION

Various approaches have been suggested to identify acute kidney injury (AKI) early and to initiate kidney-protective measures in patients at risk or with AKI. The objective of this study was to evaluate whether care bundles improve kidney outcomes in these patients.

METHODS

We conducted a systematic review of the literature to evaluate the clinical effectiveness of AKI care bundles with or without urinary biomarkers in the recognition and management of AKI. The main outcomes were major adverse kidney events (MAKEs) consisting of moderate-severe AKI, receipt of renal replacement therapy (RRT), and mortality.

RESULTS

Out of 7434 abstracts screened, 946 published studies were identified. Thirteen studies [five randomized controlled trials (RCTs) and eight non-RCTs] including 16,540 patients were eligible for inclusion in the meta-analysis. Meta-analysis showed a lower incidence of MAKE in the AKI care bundle group [odds ratio (OR) 0.73, 95% confidence interval (CI) 0.66-0.81] with differences in all 3 individual outcomes [moderate-severe AKI (OR 0.65, 95% CI 0.51-0.82), RRT (OR 0.63, 95% CI = 0.46-0.88) and mortality]. Subgroup analysis of the RCTs, all adopted biomarker-based approach, decreased the risk of MAKE (OR 0.55, 95% CI 0.41-0.74). Network meta-analysis could reveal that the incorporation of biomarkers in care bundles carried a significantly lower risk of MAKE when compared to care bundles without biomarkers (OR = 0.693, 95% CI = 0.50-0.96), while the usual care subgroup had a significantly higher risk (OR = 1.29, 95% CI = 1.09-1.52).

CONCLUSION

Our meta-analysis demonstrated that care bundles decreased the risk of MAKE, moderate-severe AKI and need for RRT in AKI patients. Moreover, the inclusion of biomarkers in care bundles had a greater impact than care bundles without biomarkers.

Care Bundle for Acute Kidney Injury in Cardiac Patients: A Cluster-Randomized Trial

Detection and timely intervention of acute kidney injury (AKI) is a major challenge worldwide. Electronic alerts for AKI may improve process- and patient-related endpoints. The present study evaluated the efficacy of an AKI electronic alert system and care bundle. This is a two-arm, prospective, cluster-randomized, controlled trial enrolling patients with AKI (KDIGO criteria) and cardiac diseases. Patients were randomly assigned to a routine care group or intervention group (DRKS-IDDRKS00017751). Two hundred patients (age 79 years, 46% female) were enrolled, with 100 patients in each group. The primary endpoint did not differ between patients in the routine care group 0.5 (-7.6-10.8) mL/min/1.73 m2 versus patients in the intervention group 1.0 (-13.5-15.1) mL/min/1.73 m2, p = 0.527. Proportions of patients in both study groups with hyperkalemia, pulmonary edema, and renal acidosis were comparable. The stop of antihypertensive medication during hypotensive periods was more frequent in patients in the intervention group compared to patients in the control group, p = 0.029. The AKI diagnosis and text module for AKI in the discharge letter were more frequently documented in patients in the intervention group (40%/48% vs. 25%/34%, p = 0.034; p = 0.044, respectively). Continued intake of RAAS inhibitors and the presence of a cardiac device were independently associated with a less pronounced decrease in eGFR from admission to the lowest value. In this RCT, electronic alerts for AKI and a care bundle improved process- but not patient-related endpoints.

Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes

RATIONALE & OBJECTIVE

Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology, and outcomes. We incorporated plasma and urine biomarker measurements to identify AKI subgroups (subphenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes.

STUDY DESIGN

Multicenter cohort study.

SETTING & PARTICIPANTS

769 hospitalized adults with AKI matched with 769 without AKI, enrolled from December 2009 to February 2015 in the ASSESS-AKI Study.

PREDICTORS

29 clinical, plasma, and urinary biomarker parameters used to identify AKI subphenotypes.

OUTCOME

Composite of major adverse kidney events (MAKE) with a median follow-up period of 4.7 years.

ANALYTICAL APPROACH

Latent class analysis (LCA) and k-means clustering were applied to 29 clinical, plasma, and urinary biomarker parameters. Associations between AKI subphenotypes and MAKE were analyzed using Kaplan-Meier curves and Cox proportional hazard models.

RESULTS

Among 769 AKI patients both LCA and k-means identified 2 distinct AKI subphenotypes (classes 1 and 2). The long-term risk for MAKE was higher with class 2 (adjusted HR, 1.41 [95% CI, 1.08-1.84]; P=0.01) compared with class 1, adjusting for demographics, hospital level factors, and KDIGO stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of long-term chronic kidney disease progression and dialysis. The top variables that were different between classes 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury; serum creatinine ranked 20th out of the 29 variables for differentiating classes.

LIMITATIONS

A replication cohort with simultaneously collected blood and urine sampling in hospitalized adults with AKI and long-term outcomes was unavailable.

CONCLUSIONS

We identify 2 molecularly distinct AKI subphenotypes with differing risk of long-term outcomes, independent of the current criteria to risk stratify AKI. Future identification of AKI subphenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI.

PLAIN-LANGUAGE SUMMARY

Acute kidney injury (AKI) occurs commonly in hospitalized patients and is associated with high morbidity and mortality. The AKI definition lumps many different types of AKI together, but subgroups of AKI may be more tightly linked to the underlying biology and clinical outcomes. We used 29 different clinical, blood, and urinary biomarkers and applied 2 different statistical algorithms to identify AKI subtypes and their association with long-term outcomes. Both clustering algorithms identified 2 AKI subtypes with different risk of chronic kidney disease, independent of the serum creatinine concentrations (the current gold standard to determine severity of AKI). Identification of AKI subtypes may facilitate linking therapies to underlying biology to prevent long-term consequences after AKI.

Medication use and hospital-acquired acute kidney injury: an electronic health record-based study

BACKGROUND AND AIMS

Medications remain an important contributor to the development of acute kidney injury (AKI). This study aimed to examine associations between (i) administration of medications known to reduce glomerular filtration rate (GFR), that is, GFR modifiers and subsequent hospital-acquired AKI; and (ii) potentially medication-related AKI and patient adverse outcomes.

METHODS

A retrospective cohort study utilising electronic health record data of patients admitted to a tertiary hospital in Australia in 2015. Timing of medication administration was compared with timing of AKI development. AKI cases were identified using an algorithm based on serum creatinine level changes. Multilevel regression models were applied with adjustment for relevant demographic and clinical factors.

RESULTS

Among 11 503 admissions, AKI was identified in 955 patients (8.3%) and 637 (66.7% of 955) were preceded by administration of a GFR modifier. Patients without prior AKI were 17% more likely to develop AKI after administration of these medications (adjusted odds ratio 1.17, 95% confidence interval (CI) 1.003-1.37). Older age and comorbidity with diabetes, acute myocardial infarction, peripheral vascular disease, liver cirrhosis and multiple myeloma were also significant predictors. Patients with potentially medication-related AKI were 11.69 times more likely to die in hospital (95% CI 7.84-17.43) and stayed 3.49 times longer in hospital (95% CI 3.26-3.73), compared with those without AKI.

CONCLUSIONS

Administration of medications contributing to the reduction of GFR is associated with an increased risk of hospital-acquired AKI and worse patient outcomes. Caution is required when prescribing these medications to patients at risk of developing AKI, and monitoring patients for deterioration is needed if administered.

Management of Acute Kidney Injury in Critically Ill Children

Acute kidney injury (AKI) is common in critically ill patients, affecting almost one in four critically ill children and one in three neonates. Higher stages of AKI portend worse outcomes. Identifying AKI timely and instituting appropriate measures to prevent and manage severe AKI is important, since it is independently associated with mortality. Methods to predict severe AKI should be applied to all critically ill patients. Assessment of volume status to prevent the development of fluid overload is useful to prevent adverse outcomes. Patients with metabolic or clinical complications of AKI need prompt kidney replacement therapy (KRT). Various modes of KRT are available, and the choice of modality depends most on the technical competence of the center, patient size, and hemodynamic stability. Given the significant risk of chronic kidney disease, patients with AKI require long-term follow-up. It is important to focus on improving awareness about AKI, incorporate AKI prevention as a quality initiative, and improve detection, prevention, and management of AKI with the aim of reducing acute and long-term morbidity and mortality.

Definitions, phenotypes, and subphenotypes in acute kidney injury-Moving towards precision medicine

The current definition of acute kidney injury (AKI) is generic and, based only on markers of function, is unsuitable for guiding individualized treatment. AKI is a complex syndrome with multiple presentations and causes. Targeted AKI management will only be possible if different phenotypes and subphenotypes of AKI are recognised, based on causation and related pathophysiology. Molecular signatures to identify subphenotypes are being recognised, as specific biomarkers reveal activated pathways. Assessment of individual clinical risk needs wider dissemination to allow identification of patients at high risk of AKI. New and more timely markers for glomerular filtration rate (GFR) are available. However, AKI diagnosis and classification should not be limited to GFR, but include tubular function and damage. Combining damage and stress biomarkers with functional markers enhances risk prediction, and identifies a population enriched for clinical trials targeting AKI. We review novel developments and aim to encourage implementation of these new techniques into clinical practice as a strategy for individualizing AKI treatment akin to a precision medicine-based approach.

Urinary sodium excretion is low prior to acute kidney injury in patients in the intensive care unit

Background

The incidence of acute kidney injury (AKI) is high in intensive care units (ICUs), and a better understanding of AKI is needed. Early chronic kidney disease is associated with urinary concentration inability and AKI recovery with increased urinary solutes in humans. Whether the inability of the kidneys to concentrate urine and excrete solutes at appropriate levels could occur prior to the diagnosis of AKI is still uncertain, and the associated mechanisms have not been studied.

Methods

In this single-center prospective observational study, high AKI risk in ICU patients was followed up for 7 days or until ICU discharge. They were grouped as "AKI" or "No AKI" according to their AKI status throughout admission. We collected daily urine samples to measure solute concentrations and osmolality. Data were analyzed 1 day before AKI, or from the first to the fifth day of admission in the "No AKI" group. We used logistic regression models to evaluate the influence of the variables on future AKI diagnosis. The expression of kidney transporters in urine was evaluated by Western blotting.

Results

We identified 29 patients as "No AKI" and 23 patients as "AKI," the latter being mostly low severity AKI. Urinary sodium excretion was lower in "AKI" patients prior to AKI diagnosis, particularly in septic patients. The expression of Na+/H+ exchanger (NHE3), a urinary sodium transporter, was higher in "AKI" patients.

Conclusions

Urinary sodium excretion is low before an AKI episode in ICU patients, and high expressions of proximal tubule sodium transporters might contribute to this.