A trial of in-hospital, electronic alerts for acute kidney injury: design and rationale

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.

Randomized elimination and prolongation of ACE inhibitors and ARBs in coronavirus 2019 (REPLACE COVID) Trial Protocol

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), is associated with high incidence of multiorgan dysfunction and death. Angiotensin-converting enzyme 2 (ACE2), which facilitates SARS-CoV-2 host cell entry, may be impacted by angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), two commonly used antihypertensive classes. In a multicenter, international randomized controlled trial that began enrollment on March 31, 2020, participants are randomized to continuation vs withdrawal of their long-term outpatient ACEI or ARB upon hospitalization with COVID-19. The primary outcome is a hierarchical global rank score incorporating time to death, duration of mechanical ventilation, duration of renal replacement or vasopressor therapy, and multiorgan dysfunction severity. Approval for the study has been obtained from the Institutional Review Board of each participating institution, and all participants will provide informed consent. A data safety monitoring board has been assembled to provide independent oversight of the project.

eHealth interventions for people with chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is associated with high morbidity and death, which increases as CKD progresses to end-stage kidney disease (ESKD). There has been increasing interest in developing innovative, effective and cost-efficient methods to engage with patient populations and improve health behaviours and outcomes. Worldwide there has been a tremendous increase in the use of technologies, with increasing interest in using eHealth interventions to improve patient access to relevant health information, enhance the quality of healthcare and encourage the adoption of healthy behaviours.

OBJECTIVES

This review aims to evaluate the benefits and harms of using eHealth interventions to change health behaviours in people with CKD.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies up to 14 January 2019 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

Randomised controlled trials (RCTs) and quasi-RCTs using an eHealth intervention to promote behaviour change in people with CKD were included. There were no restrictions on outcomes, language or publication type.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed trial eligibility, extracted data and assessed the risk of bias. The certainty of the evidence was assessed using GRADE.

MAIN RESULTS

We included 43 studies with 6617 participants that evaluated the impact of an eHealth intervention in people with CKD. Included studies were heterogeneous in terms of eHealth modalities employed, type of intervention, CKD population studied and outcomes assessed. The majority of studies (39 studies) were conducted in an adult population, with 16 studies (37%) conducted in those on dialysis, 11 studies (26%) in the pre-dialysis population, 15 studies (35%) in transplant recipients and 1 studies (2%) in transplant candidates We identified six different eHealth modalities including: Telehealth; mobile or tablet application; text or email messages; electronic monitors; internet/websites; and video or DVD. Three studies used a combination of eHealth interventions. Interventions were categorised into six types: educational; reminder systems; self-monitoring; behavioural counselling; clinical decision-aid; and mixed intervention types. We identified 98 outcomes, which were categorised into nine domains: blood pressure (9 studies); biochemical parameters (6 studies); clinical end-points (16 studies); dietary intake (3 studies); quality of life (9 studies); medication adherence (10 studies); behaviour (7 studies); physical activity (1 study); and cost-effectiveness (7 studies).Only three outcomes could be meta-analysed as there was substantial heterogeneity with respect to study population and eHealth modalities utilised. There was found to be a reduction in interdialytic weight gain of 0.13kg (4 studies, 335 participants: MD -0.13, 95% CI -0.28 to 0.01; I² = 0%) and a reduction in dietary sodium intake of 197 mg/day (2 studies, 181 participants: MD -197, 95% CI -540.7 to 146.8; I² = 0%). Both dietary sodium and fluid management outcomes were graded as being of low evidence due to high or unclear risk of bias and indirectness (interdialytic weight gain) and high or unclear risk of bias and imprecision (dietary sodium intake). Three studies reported death (2799 participants, 146 events), with 45 deaths/1000 cases compared to standard care of 61 deaths/1000 cases (RR 0.74, CI 0.53 to 1.03; P = 0.08). We are uncertain whether using eHealth interventions, in addition to usual care, impact on the number of deaths as the certainty of this evidence was graded as low due to high or unclear risk of bias, indirectness and imprecision.

AUTHORS' CONCLUSIONS

eHealth interventions may improve the management of dietary sodium intake and fluid management. However, overall these data suggest that current evidence for the use of eHealth interventions in the CKD population is of low quality, with uncertain effects due to methodological limitations and heterogeneity of eHealth modalities and intervention types. Our review has highlighted the need for robust, high quality research that reports a core (minimum) data set to enable meaningful evaluation of the literature.

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.

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.

Approaches to Predicting Outcomes in Patients with Acute Kidney Injury

Despite recognition that Acute Kidney Injury (AKI) leads to substantial increases in morbidity, mortality, and length of stay, accurate prognostication of these clinical events remains difficult. It remains unclear which approaches to variable selection and model building are most robust. We used data from a randomized trial of AKI alerting to develop time-updated prognostic models using stepwise regression compared to more advanced variable selection techniques. We randomly split data into training and validation cohorts. Outcomes of interest were death within 7 days, dialysis within 7 days, and length of stay. Data elements eligible for model-building included lab values, medications and dosages, procedures, and demographics. We assessed model discrimination using the area under the receiver operator characteristic curve and r-squared values. 2241 individuals were available for analysis. Both modeling techniques created viable models with very good discrimination ability, with AUCs exceeding 0.85 for dialysis and 0.8 for death prediction. Model performance was similar across model building strategies, though the strategy employing more advanced variable selection was more parsimonious. Very good to excellent prediction of outcome events is feasible in patients with AKI. More advanced techniques may lead to more parsimonious models, which may facilitate adoption in other settings.

False-Positive Rate of AKI Using Consensus Creatinine-Based Criteria

BACKGROUND AND OBJECTIVES

Use of small changes in serum creatinine to diagnose AKI allows for earlier detection but may increase diagnostic false-positive rates because of inherent laboratory and biologic variabilities of creatinine.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We examined serum creatinine measurement characteristics in a prospective observational clinical reference cohort of 2267 adult patients with AKI by Kidney Disease Improving Global Outcomes creatinine criteria and used these data to create a simulation cohort to model AKI false-positive rates. We simulated up to seven successive blood draws on an equal population of hypothetical patients with unchanging true serum creatinine values. Error terms generated from laboratory and biologic variabilities were added to each simulated patient's true serum creatinine value to obtain the simulated measured serum creatinine for each blood draw. We determined the proportion of patients who would be erroneously diagnosed with AKI by Kidney Disease Improving Global Outcomes creatinine criteria.

RESULTS

Within the clinical cohort, 75.0% of patients received four serum creatinine draws within at least one 48-hour period during hospitalization. After four simulated creatinine measurements that accounted for laboratory variability calculated from assay characteristics and 4.4% of biologic variability determined from the clinical cohort and publicly available data, the overall false-positive rate for AKI diagnosis was 8.0% (interquartile range =7.9%-8.1%), whereas patients with true serum creatinine ≥1.5 mg/dl (representing 21% of the clinical cohort) had a false-positive AKI diagnosis rate of 30.5% (interquartile range =30.1%-30.9%) versus 2.0% (interquartile range =1.9%-2.1%) in patients with true serum creatinine values <1.5 mg/dl (P<0.001).

CONCLUSIONS

Use of small serum creatinine changes to diagnose AKI is limited by high false-positive rates caused by inherent variability of serum creatinine at higher baseline values, potentially misclassifying patients with CKD in AKI studies.

Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial

BACKGROUND

Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital.

METHODS

In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA, USA. Eligible participants were adults aged 18 years or older who were in hospital with stage 1 or greater acute kidney injury as defined by Kidney Disease Improving Global Outcomes creatinine-based criteria. Exclusion criteria were initial hospital creatinine 4·0 mg/dL (to convert to μmol/L, multiply by 88·4) or greater, fewer than two creatinine values measured, inability to determine the covering provider, admission to hospice or the observation unit, previous randomisation, or end-stage renal disease. Patients were randomly assigned (1:1) via a computer-generated sequence to receive an acute kidney injury alert (a text-based alert sent to the covering provider and unit pharmacist indicating new acute kidney injury) or usual care, stratified by medical versus surgical admission and intensive care unit versus non-intensive care unit location in blocks of 4-8 participants. The primary outcome was a composite of relative maximum change in creatinine, dialysis, and death at 7 days after randomisation. All analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01862419.

FINDINGS

Between Sept 17, 2013, and April 14, 2014, 23,664 patients were screened. 1201 eligible participants were assigned to the acute kidney injury alert group and 1192 were assigned to the usual care group. Composite relative maximum change in creatinine, dialysis, and death at 7 days did not differ between the alert group and the usual care group (p=0·88), or within any of the four randomisation strata (all p>0·05). At 7 days after randomisation, median maximum relative change in creatinine concentrations was 0·0% (IQR 0·0-18·4) in the alert group and 0·6% (0·0-17·5) in the usual care group (p=0·81); 87 (7·2%) patients in the alert group and 70 (5·9%) patients in usual care group had received dialysis (odds ratio 1·25 [95% CI 0·90-1·74]; p=0·18); and 71 (5·9%) patients in the alert group and 61 (5·1%) patients in the usual care group had died (1·16 [0·81-1·68]; p=0·40).

INTERPRETATION

An electronic alert system for acute kidney injury did not improve clinical outcomes among patients in hospital.

FUNDING

Penn Center for Healthcare Improvement and Patient Safety.