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Updated: Apr 16, 2026

A Large Animal Model for Acute Kidney Injury by Temporary Bilateral Renal Artery Occlusion
Published on: February 2, 2021
Identifying acute kidney injury in the community--a novel informatics approach
Gang Xu1,2, Paul Player3, David Shepherd4,5
1University Hospitals of Leicester NHS Trust, Leicester, UK. Gx1@le.ac.uk.
Background:
Acute kidney injury (AKI) is a serious and common problem that is associated with high mortality. Currently nearly all efforts at improving outcomes in AKI have been focused on secondary care. We now know that a large number of patients most likely develop the condition in primary care. To our knowledge there has been no previous attempts to approach this topic from the primary care perspective.
Aim:
To test the utility of novel informatics software to identify patients with AKI in the community.
Setting And Method:
We carried out a retrospective audit of patients in one urban practice in Leicestershire using novel informatics software. The audit data was run on two occasions, once for high-risk patients between 4th July 2010 through until 30th September 2013, and once for low risk patients for the period of 27th October 2011 through until 21st January 2014.
Results:
During the period of the data collection the average practice list size was 12,420, with 235 and 19 AKI episodes in the high and low risk groups respectively. The annual AKI incidence was 27.9/1000 in the high-risk group, 1.22/1000 in the low risk group, and 10.6/1000 overall. The most common associated factor was sepsis in 170 patients, followed by dehydration in 54 patients.
Conclusion:
We have shown it is possible to identify patients with AKI in the community using informatics software. Our data suggests that AKI in the community is much more common than previously thought and demonstrates the need to better understand this condition from the primary care perspective.
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