Literature DB >> 30071528

Acute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support.

F Perry Wilson1,2, Jason H Greenberg1,3.   

Abstract

Broad adoption of electronic health record (EHR) systems has facilitated acute kidney injury (AKI) research in 2 ways. First, the detection of AKI based on changes in serum creatinine has largely replaced the sensitive but nonspecific administrative coding of AKI that predominated in earlier studies. Second, the ability to implement real-time AKI interventions such as alerts and best-practice advisories has emerged as a promising tool to fight against the harmful sequela of AKI, which include short-term adverse outcomes as well as progression to chronic kidney disease, dialysis, and death. In this review, we discuss the current state-of-the-art in EHR-based tools to predict imminent AKI, alert to the presence of AKI, and modify provider behaviors in the presence of AKI.
© 2018 S. Karger AG, Basel.

Entities:  

Keywords:  Acute renal injury; Alert; Clinical decision support; Real time modeling

Mesh:

Substances:

Year:  2018        PMID: 30071528      PMCID: PMC6165685          DOI: 10.1159/000492064

Source DB:  PubMed          Journal:  Nephron        ISSN: 1660-8151            Impact factor:   2.847


  17 in total

1.  Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery.

Authors:  Chirag R Parikh; Steven G Coca; Heather Thiessen-Philbrook; Michael G Shlipak; Jay L Koyner; Zhu Wang; Charles L Edelstein; Prasad Devarajan; Uptal D Patel; Michael Zappitelli; Catherine D Krawczeski; Cary S Passik; Madhav Swaminathan; Amit X Garg
Journal:  J Am Soc Nephrol       Date:  2011-08-11       Impact factor: 10.121

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

Authors:  F Perry Wilson; Michael Shashaty; Jeffrey Testani; Iram Aqeel; Yuliya Borovskiy; Susan S Ellenberg; Harold I Feldman; Hilda Fernandez; Yevgeniy Gitelman; Jennie Lin; Dan Negoianu; Chirag R Parikh; Peter P Reese; Richard Urbani; Barry Fuchs
Journal:  Lancet       Date:  2015-02-26       Impact factor: 79.321

3.  Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class.

Authors:  Kirsten Colpaert; Eric A Hoste; Kristof Steurbaut; Dominique Benoit; Sofie Van Hoecke; Filip De Turck; Johan Decruyenaere
Journal:  Crit Care Med       Date:  2012-04       Impact factor: 7.598

4.  Performance and limitations of administrative data in the identification of AKI.

Authors:  Morgan E Grams; Sushrut S Waikar; Blaithin MacMahon; Seamus Whelton; Shoshana H Ballew; Josef Coresh
Journal:  Clin J Am Soc Nephrol       Date:  2014-01-23       Impact factor: 8.237

5.  Identification of Patients Expected to Benefit from Electronic Alerts for Acute Kidney Injury.

Authors:  Aditya Biswas; Chirag R Parikh; Harold I Feldman; Amit X Garg; Stephen Latham; Haiqun Lin; Paul M Palevsky; Ugochukwu Ugwuowo; F Perry Wilson
Journal:  Clin J Am Soc Nephrol       Date:  2018-03-29       Impact factor: 8.237

6.  A computerized provider order entry intervention for medication safety during acute kidney injury: a quality improvement report.

Authors:  Allison B McCoy; Lemuel R Waitman; Cynthia S Gadd; Ioana Danciu; James P Smith; Julia B Lewis; Jonathan S Schildcrout; Josh F Peterson
Journal:  Am J Kidney Dis       Date:  2010-08-14       Impact factor: 8.860

7.  Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study.

Authors:  Eric A J Hoste; Sean M Bagshaw; Rinaldo Bellomo; Cynthia M Cely; Roos Colman; Dinna N Cruz; Kyriakos Edipidis; Lui G Forni; Charles D Gomersall; Deepak Govil; Patrick M Honoré; Olivier Joannes-Boyau; Michael Joannidis; Anna-Maija Korhonen; Athina Lavrentieva; Ravindra L Mehta; Paul Palevsky; Eric Roessler; Claudio Ronco; Shigehiko Uchino; Jorge A Vazquez; Erick Vidal Andrade; Steve Webb; John A Kellum
Journal:  Intensive Care Med       Date:  2015-07-11       Impact factor: 17.440

8.  Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children.

Authors:  Rajit K Basu; Michael Zappitelli; Lori Brunner; Yu Wang; Hector R Wong; Lakhmir S Chawla; Derek S Wheeler; Stuart L Goldstein
Journal:  Kidney Int       Date:  2013-09-18       Impact factor: 10.612

9.  Temporal changes in incidence of dialysis-requiring AKI.

Authors:  Raymond K Hsu; Charles E McCulloch; R Adams Dudley; Lowell J Lo; Chi-yuan Hsu
Journal:  J Am Soc Nephrol       Date:  2012-12-06       Impact factor: 10.121

10.  A risk prediction score for acute kidney injury in the intensive care unit.

Authors:  Rakesh Malhotra; Kianoush B Kashani; Etienne Macedo; Jihoon Kim; Josee Bouchard; Susan Wynn; Guangxi Li; Lucila Ohno-Machado; Ravindra Mehta
Journal:  Nephrol Dial Transplant       Date:  2017-05-01       Impact factor: 5.992

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  9 in total

1.  Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Authors:  Kumardeep Chaudhary; Akhil Vaid; Áine Duffy; Ishan Paranjpe; Suraj Jaladanki; Manish Paranjpe; Kipp Johnson; Avantee Gokhale; Pattharawin Pattharanitima; Kinsuk Chauhan; Ross O'Hagan; Tielman Van Vleck; Steven G Coca; Richard Cooper; Benjamin Glicksberg; Erwin P Bottinger; Lili Chan; Girish N Nadkarni
Journal:  Clin J Am Soc Nephrol       Date:  2020-10-08       Impact factor: 8.237

2.  Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19.

Authors:  Akhil Vaid; Lili Chan; Kumardeep Chaudhary; Suraj K Jaladanki; Ishan Paranjpe; Adam Russak; Arash Kia; Prem Timsina; Matthew A Levin; John Cijiang He; Erwin P Böttinger; Alexander W Charney; Zahi A Fayad; Steven G Coca; Benjamin S Glicksberg; Girish N Nadkarni
Journal:  Clin J Am Soc Nephrol       Date:  2021-05-24       Impact factor: 10.614

3.  Acute kidney injury risk-based screening in pediatric inpatients: a pragmatic randomized trial.

Authors:  Sara L Van Driest; Li Wang; Michael F McLemore; Brian C Bridges; Geoffrey M Fleming; Tracy L McGregor; Deborah P Jones; Jana Shirey-Rice; Cheryl L Gatto; James C Gay; Daniel W Byrne; Asli Weitkamp; Dan M Roden; Gordon Bernard
Journal:  Pediatr Res       Date:  2019-08-27       Impact factor: 3.756

4.  Rapid Multianalyte Microfluidic Homogeneous Immunoassay on Electrokinetically Driven Beads.

Authors:  Pierre-Emmanuel Thiriet; Danashi Medagoda; Gloria Porro; Carlotta Guiducci
Journal:  Biosensors (Basel)       Date:  2020-12-21

5.  Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational study.

Authors:  Christopher Bourdeaux; Erina Ghosh; Louis Atallah; Krishnamoorthy Palanisamy; Payaal Patel; Matthew Thomas; Timothy Gould; John Warburton; Jon Rivers; John Hadfield
Journal:  Crit Care       Date:  2020-11-23       Impact factor: 9.097

6.  Stakeholder Perspectives on an Inpatient Hypoglycemia Informatics Alert: Mixed Methods Study.

Authors:  Nestoras Mathioudakis; Moeen Aboabdo; Mohammed S Abusamaan; Christina Yuan; LaPricia Lewis Boyer; Scott J Pilla; Erica Johnson; Sanjay Desai; Amy Knight; Peter Greene; Sherita H Golden
Journal:  JMIR Hum Factors       Date:  2021-11-26

7.  Severe acute kidney injury predicting model based on transcontinental databases: a single-centre prospective study.

Authors:  Qiqiang Liang; Yongfeng Xu; Yu Zhou; Xinyi Chen; Juan Chen; Man Huang
Journal:  BMJ Open       Date:  2022-03-03       Impact factor: 2.692

8.  Embedded point of care randomisation for evaluating comparative effectiveness questions: PROSPECTOR-critical care feasibility study protocol.

Authors:  Matthew G Wilson; Folkert W Asselbergs; Ruben Miguel; David Brealey; Steve K Harris
Journal:  BMJ Open       Date:  2022-09-19       Impact factor: 3.006

Review 9.  Does Your Program Know Its AKI and CRRT Epidemiology? The Case for a Dashboard.

Authors:  Theresa A Mottes
Journal:  Front Pediatr       Date:  2020-03-06       Impact factor: 3.418

  9 in total

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