ArticleBMJ open2019
Electronic Alerts for Acute Kidney Injury Amelioration (ELAIA-1): a completely electronic, multicentre, randomised controlled trial: design and rationale.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02753751 (Optimizing Electronic Alerts for Acute Kidney Injury), which is not on this map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Optimizing Electronic Alerts for Acute Kidney Injury
Who cites it
13 citing papers in PubMed.
- Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial.BMJ (Clinical research ed.) · 2021Trial
- Identification of L-shaped curve association between serum bicarbonate concentrations and short-term outcomes in patients with acute kidney injury: a retrospective cohort study.Renal failure · 2025Article
- A dynamic customized electronic health record rule based clinical decision support tool for standardized adult intensive care metrics.JAMIA open · 2024Article
- Serial Urinary C-C Motif Chemokine Ligand 14 and Risk of Persistent Severe Acute Kidney Injury.Critical care explorations · 2023Article
- Performance of a Standardized Clinical Assay for Urinary C-C Motif Chemokine Ligand 14 (CCL14) for Persistent Severe Acute Kidney Injury.Kidney360 · 2022Article
- A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients.Journal of nephrology · 2021Article
- Design and rationale of the colchicine/statin for the prevention of COVID-19 complications (COLSTAT) trial.Contemporary clinical trials · 2021Article
- Diagnosis of Cardiac Surgery-Associated Acute Kidney Injury.Journal of clinical medicine · 2021Review
- The Association of COVID-19 With Acute Kidney Injury Independent of Severity of Illness: A Multicenter Cohort Study.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2021Observational
- Variation in Best Practice Measures in Patients With Severe Hospital-Acquired Acute Kidney Injury: A Multicenter Study.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2021Article
- Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2020Observational
- The impact of biomarkers of acute kidney injury on individual patient care.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2020Review
- Machine Learning to Predict Acute Kidney Injury.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2020Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
introductionAcute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack of strong evidence of their benefits. We designed a multicentre, randomised, controlled trial to evaluate the effectiveness of AKI alerts. Our aim is to highlight several challenges faced in the design of this trial, which uses electronic screening, enrolment, randomisation, intervention and data collection. METHODS AND ANALYSIS: The design and implementation of an electronic alert system for AKI was a reiterative process involving several challenges and limitations set by the confines of the electronic medical record system. The trial will electronically identify and randomise 6030 adults with AKI at six hospitals over a 1.5-2 year period to usual care versus an electronic alert containing an AKI-specific order set. Our primary outcome will be a composite of AKI progression, inpatient dialysis and inpatient death within 14 days of randomisation. During a 1-month pilot in the medical intensive care unit of Yale New Haven Hospital, we have demonstrated feasibility of automating enrolment and data collection. Feedback from providers exposed to the alerts was used to continually improve alert clarity, user friendliness and alert specificity through refined inclusion and exclusion criteria. ETHICS AND DISSEMINATION: This study has been approved by the appropriate ethics committees for each of our study sites. Our study qualified for a waiver of informed consent as it presents no more than minimal risk and cannot be feasibly conducted in the absence of a waiver. We are committed to open dissemination of our data through clinicaltrials.gov and submission of results to the NIH data sharing repository. Results of our trial will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT02753751; Pre-results.
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