Literature DB >> 22362062

Use of electronic results reporting to diagnose and monitor AKI in hospitalized patients.

Nicholas M Selby1, Lisa Crowley, Richard J Fluck, Christopher W McIntyre, John Monaghan, Nigel Lawson, Nitin V Kolhe.   

Abstract

BACKGROUND AND OBJECTIVES: Many patients with AKI are cared for by non-nephrologists. This can result in variable standards of care that contribute to poor outcomes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: To improve AKI recognition, a real-time, hospital-wide, electronic reporting system was designed based on current Acute Kidney Injury Network criteria. This system allowed prospective data collection on AKI incidence and outcomes such as mortality rate, length of hospital stay, and renal recovery. The setting was a 1139-bed teaching hospital with a tertiary referral nephrology unit.
RESULTS: An electronic reporting system was successfully introduced into clinical practice (false positive rate, 1.7%; false negative rate, 0.2%). The results showed that there were 3202 AKI episodes in 2619 patients during the 9-month study period (5.4% of hospital admissions). The in-hospital mortality rate was 23.8% and increased with more severe AKI (16.1% for stage 1 AKI versus 36.1% for stage 3) (P<0.001). More severe AKI was associated with longer length of hospital stay for stage 1 (8 days; interquartile range, 13) versus 11 days for stage 3 (interquartile range, 16) (P<0.001) and reduced chance of renal recovery (80.0% in stage 1 AKI versus 58.8% in stage 3) (P<0.001). Utility of the Acute Kidney Injury Network criteria was reduced in those with pre-existing CKD.
CONCLUSIONS: AKI is common in hospitalized patients and is associated with very poor outcomes. The successful implementation of electronic alert systems to aid early recognition of AKI across all acute specialties is one strategy that may help raise standards of care.

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Year:  2012        PMID: 22362062     DOI: 10.2215/CJN.08970911

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  96 in total

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Review 2.  Association between e-alert implementation for detection of acute kidney injury and outcomes: a systematic review.

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Review 3.  Electronic Alerts for Acute Kidney Injury.

Authors:  Michael Haase; Andreas Kribben; Walter Zidek; Jürgen Floege; Christian Albert; Berend Isermann; Bernt-Peter Robra; Anja Haase-Fielitz
Journal:  Dtsch Arztebl Int       Date:  2017-01-09       Impact factor: 5.594

4.  Predicting Inpatient Acute Kidney Injury over Different Time Horizons: How Early and Accurate?

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

Authors:  Francis Perry Wilson; Peter P Reese; Michael Gs Shashaty; Susan S Ellenberg; Yevgeniy Gitelman; Amar D Bansal; Richard Urbani; Harold I Feldman; Barry Fuchs
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6.  Acute kidney injury: Do electronic alerts for AKI improve outcomes?

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7.  Characteristics and Outcomes of Patients Discharged Home from an Emergency Department with AKI.

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8.  An Organizational-Level Program of Intervention for AKI: A Pragmatic Stepped Wedge Cluster Randomized Trial.

Authors:  Nicholas M Selby; Anna Casula; Laura Lamming; John Stoves; Yohan Samarasinghe; Andrew J Lewington; Russell Roberts; Nikunj Shah; Melanie Johnson; Natalie Jackson; Carol Jones; Erik Lenguerrand; Eileen McDonach; Richard J Fluck; Mohammed A Mohammed; Fergus J Caskey
Journal:  J Am Soc Nephrol       Date:  2019-02-21       Impact factor: 10.121

9.  Determining the incidence of drug-associated acute kidney injury in nursing home residents.

Authors:  Steven M Handler; Pui Wen Cheung; Colleen M Culley; Subashan Perera; Sandra L Kane-Gill; John A Kellum; Zachary A Marcum
Journal:  J Am Med Dir Assoc       Date:  2014-05-10       Impact factor: 4.669

10.  Incidence rate, clinical correlates, and outcomes of AKI in patients admitted to a comprehensive cancer center.

Authors:  Abdulla K Salahudeen; Simit M Doshi; Tushar Pawar; Gul Nowshad; Amit Lahoti; Pankaj Shah
Journal:  Clin J Am Soc Nephrol       Date:  2012-12-14       Impact factor: 8.237

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