Background And Aims: Acute kidney injury (AKI) is associated with higher mortality and length of stay (LOS) for hospitalized patients. To improve outcomes, an electronic detection system could be a useful tool for early diagnosis.

Methods: A fully automated real-time system for detecting decreased glomerular filtration rate in adult patients was developed in our hospital, DETECT-H project. AKI was established according to KDIGO guidelines.

Results: In six months, 1241 alerts from 11,022 admissions were issued. Overall incidence of AKI was 7.7%. Highest AKI stage reached was: stage 1 (49.8%), 2 (24.5%) and 3 (25.8%), in-hospital mortality was 10.9%, 22.7%, 33.9% respectively and 57.1% in AKI requiring dialysis; mortality in stable CKD was 4.3%. Median LOS was 8 days versus 5 days for all patients. AKI was associated with a mortality of 3.18 (95% CI 1.80-5.59) and a LOS 1.52 (1.11-2.08) times as high as that for admissions without AKI. Multivariate analysis indicated that a LOS higher than 8 days was associated with AKI. Previous CKD was noted in 31.9% and AKI in 45.3% at discharge. As compared to the use of the detect system, only one third of CKD patients and half of AKI episodes were identified.

Conclusions: CKD and in-hospital AKI are under-recognized entities. Mortality and LOS are increased in-hospital patients with renal dysfunction. AKI severity was associated with higher mortality and LOS. An automated electronic detection system for identifying renal dysfunction would be a useful tool to improve renal outcomes.

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Source
http://dx.doi.org/10.1016/j.nefro.2018.08.011DOI Listing

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