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

Acute Kidney Injury Provider and Survivor Education: Current and Emerging Tools

Acute kidney injury (AKI) is associated with an increased risk of adverse health outcomes, but the proportion of patients receiving optimal care is low. Barriers to improving outcomes after AKI include limited recognition of AKI by providers, the required transitions of care from the inpatient and outpatient settings, and lack of patient awareness of the AKI event. Gaps in the care of AKI survivors may be improved with enhanced education for providers and patients. Some tools focused on early detection of AKI and improving AKI management have been developed with variable success in addressing adverse outcomes. Significant heterogeneity within the AKI population and complexities of care coordination continue to hinder programs focused on improving AKI survivorship. On the horizon, promising programs are emerging that may overcome these barriers by offering an individualized, patient-centered approach to AKI survivorship by integrating technological advances and multidisciplinary support. Greater emphasis is being placed on ensuring that tactics for AKI management can be implemented beyond the nephrology subspecialty. These programs can potentially prevent AKI, optimize recovery, and increase patient satisfaction. This review discusses the current and emerging educational resources for AKI survivors and their providers.

Effect of Tiered Implementation of Clinical Decision Support System for Acute Kidney Injury and Nephrotoxin Exposure in Cardiac Surgery Patients

BACKGROUND

 Nephrotoxin exposure may worsen kidney injury and impair kidney recovery if continued in patients with acute kidney injury (AKI).

OBJECTIVES

 This study aimed to determine if tiered implementation of a clinical decision support system (CDSS) would reduce nephrotoxin use in cardiac surgery patients with AKI.

METHODS

 We assessed patients admitted to the cardiac surgery intensive care unit at a tertiary care center from January 2020 to December 2021, and August 2022 to September 2023. A passive electronic AKI alert was activated in July 2020, followed by an electronic nephrotoxin alert in March 2023. In this alert, active nephrotoxic medication orders resulted in a passive alert, whereas new orders were met with an interruptive alert. Primary outcome was discontinuation of nephrotoxic medications within 30 hours after AKI. Secondary outcomes included AKI-specific clinical actions, determined through modified Delphi process and patient-centered outcomes. We compared all outcomes across five separate eras, divided based on the tiered implementation of these alerts.

RESULTS

 A total of 503 patients met inclusion criteria. Of 114 patients who received nephrotoxins before AKI, nephrotoxins were discontinued after AKI in 6 (25%) patients in pre AKI-alert era, 8 (33%) patients in post AKI-alert era, 7 (35%) patients in AKI-alert long-term follow up era, 7 (35%) patients in pre nephrotoxin-alert era, and 14 (54%) patients in post nephrotoxin-alert era (p = 0.047 for trend). Among AKI-specific consensus actions, we noted a decreased use of intravenous fluids, increased documentation of goal mean arterial pressure of 65 mm Hg or higher, and increased use of bedside point of care echocardiogram over time. Among exploratory clinical outcomes we found a decrease in proportion of stage III AKI, need for dialysis, and length of hospital stay over time.

CONCLUSION

 Tiered implementation of CDSS for recognition of AKI and nephrotoxin exposure resulted in a progressive improvement in the discontinuation of nephrotoxins.

Early, Individualized Recommendations for Hospitalized Patients With Acute Kidney Injury: A Randomized Clinical Trial

Importance

Acute kidney injury (AKI) is a common complication during hospitalization and is associated with adverse outcomes.

Objective

To evaluate whether diagnostic and therapeutic recommendations sent by a kidney action team through the electronic health record improve outcomes among patients hospitalized with AKI compared with usual care.

Design, Setting, and Participants

Randomized clinical trial conducted at 7 hospitals in 2 health systems: in New Haven, Bridgeport, New London, and Waterbury, Connecticut, and Westerly, Rhode Island; and in Baltimore, Maryland. Hospitalized patients with AKI were randomized between October 29, 2021, and February 8, 2024. Final follow-up occurred February 22, 2024.

Intervention

An alert about AKI was sent to the kidney action team, consisting of a study physician and study pharmacist, which sent personalized recommendations through the electronic health record in 5 major categories (diagnostic testing, volume, potassium, acid base, and medications) within 1 hour of AKI detection. The note was immediately visible to anyone with access to the electronic health record. Randomization to the intervention or usual care occurred after the recommendations were generated, but the note was only delivered to clinicians of patients randomized to the intervention group.

Main Outcomes and Measures

The primary outcome was a composite outcome consisting of AKI progression to a higher stage of AKI, dialysis, or mortality occurring while the patient remained hospitalized and within 14 days from randomization.

Results

Of the 4003 patients randomized (median age, 72 years [IQR, 61-81 years), 1874 (47%) were female and 931 (23%) were Black patients. The kidney action team made 14 539 recommendations, with a median of 3 (IQR, 2-5) per patient. The primary outcome occurred in 19.8% of the intervention group and in 18.4% in the usual care group (difference, 1.4%, 95% CI, -1.1% to 3.8,% P = .28). Of 6 secondary outcomes, only 1 secondary outcome, rates of recommendation implementation, significantly differed between the 2 groups: 2459 of 7270 recommendations (33.8%) were implemented in the intervention group and 1766 of 7269 undelivered recommendations (24.3%) were implemented in the usual care group within 24 hours (difference, 9.5%; 95% CI, 8.1% to 11.0%).

Conclusions and Relevance

Among patients hospitalized with AKI, recommendations from a kidney action team did not significantly reduce the composite outcome of worsening AKI stage, dialysis, or mortality, despite a higher rate of recommendation implementation in the intervention group than in the usual care group.

Trial Registration

ClinicalTrials.gov Identifier: NCT04040296.

The effect of clinical decision support systems on clinical outcomes in acute kidney injury: a systematic review and meta-analysis of randomized controlled trials

OBJECTIVES

To determine whether clinical decision support systems (CDSS) for acute kidney injury (AKI) would enhance patient outcomes in terms of mortality, dialysis, and acute kidney damage progression.

METHODS

The systematic review and meta-analysis included the relevant randomized controlled trials (RCTs) retrieved from PubMed, EMBASE, Web of Science, Cochrane, and SCOPUS databases until 21st January 2024. The meta-analysis was done using (RevMan 5.4.1). PROSPERO ID: CRD42024517399.

RESULTS

Our meta-analysis included ten RCTs with 18,355 patients. There was no significant difference between CDSS and usual care in all-cause mortality (RR: 1.00 with 95% CI [0.93, 1.07], p = 0.91) and renal replacement therapy (RR: 1.11 with 95% CI [0.99, 1.24], p = 0.07). However, CDSS was significantly associated with a decreased incidence of hyperkalemia (RR: 0.27 with 95% CI [0.10, 0.73], p = 0.01) and increased eGFR change (MD: 1.97 with 95% CI [0.47, 3.48], p = 0.01).

CONCLUSIONS

CDSS were not associated with clinical benefit in patients with AKI, with no effect on all-cause mortality or the need for renal replacement therapy. However, CDSS reduced the incidence of hyperkalemia and improved eGFR change in AKI patients.

Effect of electronic alerts on the care and outcomes in patients with acute kidney injury: a meta-analysis and trial sequential analysis

BACKGROUND

Although electronic alerts are being increasingly implemented in patients with acute kidney injury (AKI), their effect remains unclear. Therefore, we conducted this meta-analysis aiming at investigating their impact on the care and outcomes of AKI patients.

METHODS

PubMed, Embase, Cochrane Library, and Clinical Trial Registries databases were systematically searched for relevant studies from inception to March 2024. Randomized controlled trials comparing electronic alerts with usual care in patients with AKI were selected.

RESULTS

Six studies including 40,146 patients met the inclusion criteria. The pooled results showed that electronic alerts did not improve mortality rates (relative risk (RR) = 1.02, 95% confidence interval (CI) = 0.97-1.08, P = 0.44) or reduce creatinine levels (mean difference (MD) =  - 0.21, 95% CI =  - 1.60-1.18, P = 0.77) and AKI progression (RR = 0.97, 95% CI = 0.90-1.04, P = 0.40). Instead, electronic alerts increased the odds of dialysis and AKI documentation (RR = 1.14, 95% CI = 1.05-1.25, P = 0.002; RR = 1.21, 95% CI = 1.01-1.44, P = 0.04, respectively), but the trial sequential analysis (TSA) could not confirm these results. No differences were observed in other care-centered outcomes including renal consults and investigations between the alert and usual care groups.

CONCLUSIONS

Electronic alerts increased the incidence of AKI and dialysis in AKI patients, which likely reflected improved recognition and early intervention. However, these changes did not improve the survival or kidney function of AKI patients. The findings warrant further research to comprehensively evaluate the impact of electronic alerts.

Acceptance and use of a clinical decision support system in musculoskeletal pain disorders - the SupportPrim project

BACKGROUND

We have developed a clinical decision support system (CDSS) based on methods from artificial intelligence to support physiotherapists and patients in the decision-making process of managing musculoskeletal (MSK) pain disorders in primary care. The CDSS finds the most similar successful patients from the past to give treatment recommendations for a new patient. Using previous similar patients with successful outcomes to advise treatment moves management of MSK pain patients from one-size fits all recommendations to more individually tailored treatment. This study aimed to summarise the development and explore the acceptance and use of the CDSS for MSK pain patients.

METHODS

This qualitative study was carried out in the Norwegian physiotherapy primary healthcare sector between October and November 2020, ahead of a randomised controlled trial. We included four physiotherapists and three of their patients, in total 12 patients, with musculoskeletal pain in the neck, shoulder, back, hip, knee or complex pain. We conducted semi-structured telephone interviews with all participants. The interviews were analysed using the Framework Method.

RESULTS

Overall, both the physiotherapists and patients found the system acceptable and usable. Important findings from the analysis of the interviews were that the CDSS was valued as a preparatory and exploratory tool, facilitating the therapeutic relationship. However, the physiotherapists used the system mainly to support their previous and current practice rather than involving patients to a greater extent in decisions and learning from previous successful patients.

CONCLUSIONS

The CDSS was acceptable and usable to both the patients and physiotherapists. However, the system appeared not to considerably influence the physiotherapists' clinical reasoning and choice of treatment based on information from most similar successful patients. This could be due to a smaller than optimal number of previous patients in the CDSS or insufficient clinical implementation. Extensive training of physiotherapists should not be underestimated to build understanding and trust in CDSSs.

Personalised recommendations for hospitalised patients with Acute Kidney Injury using a Kidney Action Team (KAT-AKI): protocol and early data of a randomised controlled trial

INTRODUCTION

Although studies have examined the utility of clinical decision support tools in improving acute kidney injury (AKI) outcomes, no study has evaluated the effect of real-time, personalised AKI recommendations. This study aims to assess the impact of individualised AKI-specific recommendations delivered by trained clinicians and pharmacists immediately after AKI detection in hospitalised patients.

METHODS AND ANALYSIS

KAT-AKI is a multicentre randomised investigator-blinded trial being conducted across eight hospitals at two major US hospital systems planning to enrol 4000 patients over 3 years (between 1 November 2021 and 1 November 2024). A real-time electronic AKI alert system informs a dedicated team composed of a physician and pharmacist who independently review the chart in real time, screen for eligibility and provide combined recommendations across the following domains: diagnostics, volume, potassium, acid-base and medications. Recommendations are delivered to the primary team in the alert arm or logged for future analysis in the usual care arm. The planned primary outcome is a composite of AKI progression, dialysis and mortality within 14 days from randomisation. A key secondary outcome is the percentage of recommendations implemented by the primary team within 24 hours from randomisation. The study has enrolled 500 individuals over 8.5 months. Two-thirds were on a medical floor at the time of the alert and 17.8% were in an intensive care unit. Virtually all participants were recommended for at least one diagnostic intervention. More than half (51.6%) had recommendations to discontinue or dose-adjust a medication. The median time from AKI alert to randomisation was 28 (IQR 15.8-51.5) min.

ETHICS AND DISSEMINATION

The study was approved by the ethics committee of each study site (Yale University and Johns Hopkins institutional review board (IRB) and a central IRB (BRANY, Biomedical Research Alliance of New York). We are committed to open dissemination of the data through clinicaltrials.gov and sharing of data on an open repository as well as publication in a peer-reviewed journal on completion.

TRIAL REGISTRATION NUMBER

NCT04040296.

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

BACKGROUND

Early recognition of hospital-acquired acute kidney injury (AKI) may improve patient management and outcomes.

METHODS

This multicentre study was conducted at three hospitals (H1-intervention; H2 and H3-controls) served by a single laboratory. The intervention bundle [an interruptive automated alerts (aAlerts) showing AKI stage and baseline creatinine in the eMR, a management guide and junior medical staff education] was implemented only at H1. Outcome variables included length-of-stay (LOS), all-cause in-hospital mortality and management quality.

RESULTS

Over 6 months, 639 patients developed AKI (265 at H1 and 374 at controls), with 94.7% in general wards; 537 (84%) patients developed Stage 1, 58 (9%) Stage 2 and 43 (7%) Stage 3 AKI. Median LOS was 9 days (IQR 4-17) and was not different between intervention and controls. However, patients with AKI stage 1 had shorter LOS at H1 [median 8 versus 10 days (P = 0.021)]. Serum creatinine had risen prior to admission in most patients. Documentation of AKI was better in H1 (94.8% versus 83.4%; P = 0.001), with higher rates of nephrology consultation (25% versus 19%; P = 0.04) and cessation of nephrotoxins (25.3 versus 18.8%; P = 0.045). There was no difference in mortality between H1 versus controls (11.7% versus 13.0%; P = 0.71).

CONCLUSIONS

Most hospitalized patients developed Stage 1 AKI and developed AKI in the community and remained outside the intensive care unit (ICU). The AKI eAlert bundle reduced LOS in most patients with AKI and increased AKI documentation, nephrology consultation rate and cessation of nephrotoxic medications.

Laboratory Diagnostic of Acute Kidney Injury and Its Progression: Risk of Underdiagnosis in Female and Elderly Patients

Acute kidney injury (AKI) is a common disease, with high morbidity and mortality rates. In this study, we investigated the potential influence of sex and age on laboratory diagnostics and outcomes. It is known that serum creatinine (SCr) has limitations as a laboratory diagnostic parameter for AKI due to its dependence on muscle mass, which may lead to an incorrect or delayed diagnosis for certain patient groups, such as women and the elderly. Overall, 7592 cases with AKI, hospitalized at the University of Leipzig Medical Center (ULMC) between 1st January 2017 and 31st December 2019, were retrospectively analyzed. The diagnosis and staging of AKI were performed according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, based on the level and dynamics of SCr. The impact of sex and age was analyzed by the recalculation of a female to male and an old to young SCr using the CKD-EPI equation. In our study cohort progressive AKI occurred in 19.2% of all cases (n = 1458). Female cases with AKI were underrepresented (40.4%), with a significantly lower first (-3.5 mL/min) and last eGFR (-2.7 mL/min) (p < 0.001). The highest incidence proportion of AKI was found in the [61-81) age group in female (49.5%) and male (52.7%) cases. Females with progressive AKI were underrepresented (p = 0.04). By defining and staging AKI on the basis of relative and absolute changes in the SCr level, it is more difficult for patients with low muscle mass and, thus, a lower baseline SCr to be diagnosed by an absolute SCr increase. AKIN1 and AKIN3 can be diagnosed by a relative or absolute change in SCr. In females, both stages were less frequently detected by an absolute criterion alone (AKIN1 ♀ 20.2%, ♂ 29.5%, p < 0.001; AKIN3 ♀ 13.4%, ♂ 15.2%, p < 0.001). A recalculated SCr for females (as males) and males (as young males) displayed the expected increase in AKI occurrence and severity with age and, in general, in females. Our study illustrates how SCr, as the sole parameter for the diagnosis and staging of AKI, bears the risk of underdiagnosis of patient groups with low muscle mass, such as women and the elderly. A sex- and age-adapted approach might offer advantages.

Artificial intelligence for the prediction of acute kidney injury during the perioperative period: systematic review and Meta-analysis of diagnostic test accuracy

BACKGROUND

Acute kidney injury (AKI) is independently associated with morbidity and mortality in a wide range of surgical settings. Nowadays, with the increasing use of electronic health records (EHR), advances in patient information retrieval, and cost reduction in clinical informatics, artificial intelligence is increasingly being used to improve early recognition and management for perioperative AKI. However, there is no quantitative synthesis of the performance of these methods. We conducted this systematic review and meta-analysis to estimate the sensitivity and specificity of artificial intelligence for the prediction of acute kidney injury during the perioperative period.

METHODS

Pubmed, Embase, and Cochrane Library were searched to 2nd October 2021. Studies presenting diagnostic performance of artificial intelligence in the early detection of perioperative acute kidney injury were included. True positives, false positives, true negatives and false negatives were pooled to collate specificity and sensitivity with 95% CIs and results were portrayed in forest plots. The risk of bias of eligible studies was assessed using the PROBAST tool.

RESULTS

Nineteen studies involving 304,076 patients were included. Quantitative random-effects meta-analysis using the Rutter and Gatsonis hierarchical summary receiver operating characteristics (HSROC) model revealed pooled sensitivity, specificity, and diagnostic odds ratio of 0.77 (95% CI: 0.73 to 0.81),0.75 (95% CI: 0.71 to 0.80), and 10.7 (95% CI 8.5 to 13.5), respectively. Threshold effect was found to be the only source of heterogeneity, and there was no evidence of publication bias.

CONCLUSIONS

Our review demonstrates the promising performance of artificial intelligence for early prediction of perioperative AKI. The limitations of lacking external validation performance and being conducted only at a single center should be overcome.

TRIAL REGISTRATION

This study was not registered with PROSPERO.

Derivation and evaluation of baseline creatinine equations for hospitalized children and adolescents: the AKI baseline creatinine equation

BACKGROUND

Acute kidney injury (AKI) definitions incorporate baseline creatinine (Cr_b) values, but Cr_b are frequently unknown in pediatrics. Our primary aim was to derive and validate a novel AKI Baseline Creatinine (ABC) estimation equation and compare it to existing methods of estimating Cr_b values.

METHODS

We conducted a single-center retrospective analysis of pediatric patients (0-25 years) admitted from 2012 to 2019. Included patients required at least one outpatient Cr_b prior to hospitalization (gold standard). Novel equations were developed with demographic and initial creatinine data. Existing methods included back-calculating Cr_b based on Schwartz, Full Age Spectrum (FAS), and CKiD-under-25 (U25) equations. To determine an optimal equation, we compared novel and existing equations to the gold standard.

RESULTS

The optimal simplified equation (ABC) included only age and had R² = 59.9% and 73.2% of values within 30% of true Cr_b. The precision increased significantly when the equation included age and minimum creatinine within initial 72 h (ABC-cr): R² = 75.4% and 86.5% of values within 30% of true Cr_b. The best performing existing equation was the age-based FAS, which had R² = 61.0% and 78.0% of values within 30% of true Cr_b. All other existing equations performed worse, some methods as low as 52.6% within 30% of true Cr_b.

CONCLUSIONS

The newly derived ABC equation is simple, and the ABC-cr equation can more accurately estimate Cr_b by ≥ 25% compared to previous methods. The potential applicability of these equations is vast, including faster recognition of AKI on initial patient contact and improved standardization of pediatric AKI definitions, enhancing health services research. A higher resolution version of the Graphical abstract is available as Supplementary information.

Clinical Informatics and Quality Improvement in the Pediatric Intensive Care Unit

Clinical informatics can support quality improvement and patient safety in the pediatric intensive care unit (PICU) in several ways including data extraction, analysis, and decision support enabled by electronic health records (EHRs), and databases and registries. Clinical decision support (CDS), embedded in EHRs, now an integral part of the workflow in the PICU, includes several tools and is increasingly leveraging artificial intelligence (AI). Understanding the opportunities and challenges can improve the engagement of clinicians with the design, validation, and implementation of CDS, improve satisfaction with CDS, and improve patient safety, care quality, and value.