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Background: Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. Methods and findings: A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014–16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981–1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858–0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560–0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. Conclusions: In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness. Trial registration: Clinicaltrials.org . [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Reconfiguring acute hospitals in England," by C. Ham in the December 2, 2006 issue.

Objective: The objective of this study was to externally validate a clinical prediction rule (CPR)-the 'Shapiro criteria'-to predict bacteraemia in an acute medical unit (AMU)., Methods: Prospectively collected data, retrospectively evaluated over 11 months in an AMU in the UK. From 4810 admissions, 635 patients (13%) had blood cultures (BCs) performed. The 100 cases of true bacteraemia were compared with a randomly selected sample of 100 control cases where BCs were sterile., Results: To predict bacteraemia (at a cut-off score of two points), the Shapiro criteria had a sensitivity of 97% (95% CIs 91% to 99%), specificity 37% (28% to 47%), positive likelihood ratio 1.54 (1.3 to 1.8) and a negative likelihood ratio of 0.08 (0.03 to 0.25). The area under the receiver operating curve was 0.80 (0.74 to 0.86), and the Hosmer-Lemeshow p value was 0.45., Conclusions: A cut-off score of two points on the Shapiro criteria had high sensitivity to predict bacteraemia in a study of acute general medical admissions. Application of the rule in patients being considered for a BC could identify those at low risk of bacteraemia. Though the model demonstrated good discrimination, the lengthy number of variables (13) and difficulty automating the CPR may limit its use., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)