Literature DB >> 24914088

Optimal and early detection of acute kidney injury requires effective clinical decision support systems.

Steven M Handler1, Sandra L Kane-Gill2, John A Kellum3.   

Abstract

Entities:  

Keywords:  acute kidney injury; decision support systems; electronic medical record

Mesh：

Year:  2014        PMID： 24914088     DOI： 10.1093/ndt/gfu211

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN： 0931-0509            Impact factor:   5.992


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  5 in total

1.  Impact of Compliance with a Care Bundle on Acute Kidney Injury Outcomes: A Prospective Observational Study.

Authors:  Nitin V Kolhe; David Staples; Timothy Reilly; Daniel Merrison; Christopher W Mcintyre; Richard J Fluck; Nicholas M Selby; Maarten W Taal
Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

2.  Acute kidney injury-how does automated detection perform?

Authors:  Simon Sawhney; Nick Fluck; Angharad Marks; Gordon Prescott; William Simpson; Laurie Tomlinson; Corri Black
Journal:  Nephrol Dial Transplant       Date:  2015-04-28       Impact factor: 5.992

Review 3.  Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review.

Authors:  Christian Nusshag; Markus A Weigand; Martin Zeier; Christian Morath; Thorsten Brenner
Journal:  Int J Mol Sci       Date:  2017-06-28       Impact factor: 5.923

4.  Impact of Daily Electronic Laboratory Alerting on Early Detection and Clinical Documentation of Acute Kidney Injury in Hospital Settings.

Authors:  Tarush Kothari; Kendal Jensen; Debbie Mallon; Gerard Brogan; James Crawford
Journal:  Acad Pathol       Date:  2018-12-04

5.  Safety Lapses Prior to Initiation of Hemodialysis for Acute Kidney Injury in Hospitalized Patients: A Patient Safety Initiative.

Authors:  Adrianna Douvris; Khalid Zeid; Swapnil Hiremath; Pierre Antoine Brown; Manish M Sood; Rima Abou Arkoub; Gurpreet Malhi; Edward G Clark
Journal:  J Clin Med       Date:  2018-10-01       Impact factor: 4.241
  5 in total

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