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Predicting AKI in emergency admissions: An external validation study of the acute kidney injury prediction score (APS)

Hodgson, L.E., Dimitrov, B.D., Roderick, P.J., Venn, R. and Forni, L.G. (2017) Predicting AKI in emergency admissions: An external validation study of the acute kidney injury prediction score (APS) BMJ Open, 7 (3), e013511.

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Hospital-acquired acute kidney injury (HA-AKI) is associated with a high risk of mortality. Prediction models or rules may identify those most at risk of HA-AKI. This study externally validated one of the few clinical prediction rules (CPRs) derived in a general medicine cohort using clinical information and data from an acute hospitals electronic system on admission: the acute kidney injury prediction score (APS).

Design, setting and participants:

External validation in a single UK non-specialist acute hospital (2013–2015, 12 554 episodes); four cohorts: adult medical and general surgical populations, with and without a known preadmission baseline serum creatinine (SCr).


Performance assessed by discrimination using area under the receiver operating characteristic curves (AUCROC) and calibration.


HA-AKI incidence within 7 days (kidney disease: improving global outcomes (KDIGO) change in SCr) was 8.1% (n=409) of medical patients with known baseline SCr, 6.6% (n=141) in those without a baseline, 4.9% (n=204) in surgical patients with baseline and 4% (n=49) in those without. Across the four cohorts AUCROC were: medical with known baseline 0.65 (95% CIs 0.62 to 0.67) and no baseline 0.71 (0.67 to 0.75), surgical with baseline 0.66 (0.62 to 0.70) and no baseline 0.68 (0.58 to 0.75). For calibration, in medicine and surgical cohorts with baseline SCr, Hosmer-Lemeshow p values were nonsignificant, suggesting acceptable calibration. In the medical cohort, at a cut-off of five points on the APS to predict HA-AKI, positive predictive value was 16% (13–18%) and negative predictive value 94% (93–94%). Of medical patients with HA-AKI, those with an APS ≥5 had a significantly increased risk of death (28% vs 18%, OR 1.8 (95% CI 1.1 to 2.9), p=0.015).


On external validation the APS on admission shows moderate discrimination and acceptable calibration to predict HA-AKI and may be useful as a severity marker when HA-AKI occurs. Harnessing linked data from primary care may be one way to achieve more accurate risk prediction.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Biosciences and Medicine
Authors :
Hodgson, L.E.
Dimitrov, B.D.
Roderick, P.J.
Venn, R.
Date : 8 March 2017
DOI : 10.1136/bmjopen-2016-013511
Copyright Disclaimer : Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work noncommercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://
Depositing User : Diane Maxfield
Date Deposited : 10 Oct 2019 13:52
Last Modified : 10 Oct 2019 13:52

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