Trial reportInternational urology and nephrology2018
Value of electronic alerts for acute kidney injury in high-risk wards: a pilot randomized controlled trial.
Trial report in International urology and nephrology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The influence of electronic AKI alert on prognosis of adult hospitalized patients: a systematic review and meta-analysis.Critical care (London, England) · 2025Pooled it
- Electronic Alert Systems for Patients With Acute Kidney Injury: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- Effect of clinical decision support systems on clinical outcome for acute kidney injury: a systematic review and meta-analysis.BMC nephrology · 2021Pooled it
- The effects of on-screen, point of care computer reminders on processes and outcomes of care.The Cochrane database of systematic reviews · 2009Pooled it
- Automated Electronic Alert for the Care and Outcomes of Adults With Acute Kidney Injury: A Randomized Clinical Trial.JAMA network open · 2024Trial
- The Effects of Intensive Versus Routine Treatment in Patients with Acute Kidney Injury.Deutsches Arzteblatt international · 2020Trial
- The computerized algorithm for renal assessment improves diagnostic accuracy of renal impairment in hospitalized patients.Scientific reports · 2025Article
- A Review of Electronic Early Warning Systems for Acute Kidney Injury.Advances in urology · 2024Review
- Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup.Nature reviews. Nephrology · 2023Review
- Care Bundle for Acute Kidney Injury in Cardiac Patients: A Cluster-Randomized Trial.Journal of clinical medicine · 2023Article
- Chinese experts' consensus on the application of intensive care big data.Frontiers in medicine · 2023Article
- A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients.Journal of nephrology · 2021Article
- Does Artificial Intelligence Make Clinical Decision Better? A Review of Artificial Intelligence and Machine Learning in Acute Kidney Injury Prediction.Healthcare (Basel, Switzerland) · 2021Review
- Scoping review exploring the impact of digital systems on processes and outcomes in the care management of acute kidney injury and progress towards establishing learning healthcare systems.BMJ health & care informatics · 2021Article
- Opportunities in the cloud or pie in the sky? Current status and future perspectives of telemedicine in nephrology.Clinical kidney journal · 2021Review
- Evaluation of a digitally-enabled care pathway for acute kidney injury management in hospital emergency admissions.NPJ digital medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeTo investigate the application value of "electronic alerts" ("e-alerts") for acute kidney injury (AKI) among high-risk wards of hospitals.
methodsA prospective, randomized, controlled study was conducted. We developed an e-alert system for AKI and ran the system in intensive care units and divisions focusing on cardiovascular disease. The e-alert system diagnosed AKI automatically based on serum creatinine levels. Patients were assigned randomly to an e-alert group (467 patients) or non-e-alert group (408 patients). Only the e-alert group could receive pop-up messages.
resultsThe sensitivity, specificity, Youden Index and accuracy of the AKI e-alert system were 99.8, 97.7, 97.5 and 98.1%, respectively. The prevalence of the diagnosis for AKI and expanded-AKI (AKI or multiple-organ failure) in the e-alert group was higher than that in the non-e-alert group (AKI 7.9 and 2.7%, P = 0.001; expanded-AKI 16.3 and 6.1%, P < 0.001). The prevalence of nephrology consultation in the e-alert group was higher than that in the non-e-alert group (9.0 and 3.7%, P = 0.001). There was no significant difference in the prevalence dialysis, rehabilitation of renal function or death in the two groups.
conclusionThe e-alert system described here was a reliable tool to make an accurate diagnosis of AKI.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.