Evidence map›Paper›PMID 26925246›Full record

ReviewCanadian journal of kidney health and disease2016

Impact of electronic-alerting of acute kidney injury: workgroup statements from the 15(th) ADQI Consensus Conference.

Eric A J Hoste, Kianoush Kashani, Noel Gibney, F Perry Wilson, Claudio Ronco, Stuart L Goldstein, John A Kellum, Sean M Bagshaw, 15 ADQI Consensus Group

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Canadian journal of kidney health and disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  6. Association between e-alert implementation for detection of acute kidney injury and outcomes: a systematic review.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2017
    Pooled it
  7. Electronic Alerts for Acute Kidney Injury.Deutsches Arzteblatt international · 2017
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Eric A J HosteIntensive Care Unit, Ghent University Hospital, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium ; Research Foundation-Flanders (FWO), Brussels, Belgium.
Kianoush KashaniDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, 200 First St, SW, Rochester, MN USA ; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, 200 First St, SW, Rochester, MN USA.
Noel GibneyDivision of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, CSB 2-124, 8440-112 Street, Edmonton, AB Canada.
F Perry WilsonProgram of Applied Translational Research, Department of Medicine, Yale University School of Medicine, 60 Temple Street Suite 6C, New Haven, CT 06510 USA.
Claudio RoncoDepartment of Nephrology and International Renal Research Institute, Ospedale San Bortolo, Vicenza, Italy.
Stuart L GoldsteinCenter for Acute Care Nephrology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7022, Cincinnati, OH 45229 USA.
John A KellumCenter for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA USA.
Sean M BagshawDivision of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, 8440-112 ST NW, Edmonton, AB T6G2B7 Canada.
15 ADQI Consensus Group

Funding

Mediators & prognostic value of muscle mass & function in chronic kidney diseaseK23DK097201 · NIDDK · YALE UNIVERSITY · PI WILSON, FRANCIS PERRY · 2013 to 2017
$916k
NIDDK NIH HHS K23 DK097201
6 · The paper itself

Abstract

purpose of the reviewAmong hospitalized patients, acute kidney injury is common and associated with significant morbidity and risk for mortality. The use of electronic health records (EHR) for prediction and detection of this important clinical syndrome has grown in the past decade. The steering committee of the 15(th) Acute Dialysis Quality Initiative (ADQI) conference dedicated a workgroup with the task of identifying elements that may impact the course of events following Acute Kidney Injury (AKI) e-alert. SOURCES OF INFORMATION: Following an extensive, non-systematic literature search, we used a modified Delphi process to reach consensus regarding several aspects of the utilization of AKI e-alerts.

findingsTopics discussed in this workgroup included progress in evidence base practices, the characteristics of an optimal e-alert, the measures of efficacy and effectiveness, and finally what responses would be considered best practices following AKI e-alerts. Authors concluded that the current evidence for e-alert system efficacy, although growing, remains insufficient. Technology and human-related factors were found to be crucial elements of any future investigation or implementation of such tools. The group also concluded that implementation of such systems should not be done without a vigorous plan to evaluate the efficacy and effectiveness of e-alerts. Efficacy and effectiveness of e-alerts should be measured by context-specific process and patient outcomes. Finally, the group made several suggestions regarding the clinical decision support that should be considered following successful e-alert implementation. LIMITATIONS: This paper reflects the findings of a non-systematic review and expert opinion. IMPLICATIONS: We recommend implementation of the findings of this workgroup report for use of AKI e-alerts.

Indexed as

Acute kidney injuryElectronic alertElectronic health recordsSniffer

Identifiers

PMID26925246
PMCPMC4768416

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.