• Adil Ahmed, Srinivasan Vairavan, Abbasali Akhoundi, Gregory Wilson, Caitlyn Chiofolo, Nicolas Chbat, Rodrigo Cartin-Ceba, Guangxi Li, and Kianoush Kashani.
• Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Wichita Falls Family Practice Residency Program (WFFRP), North Central Texas Medical Foundation, Wichita Falls, TX.
• J Crit Care. 2015 Oct 1; 30 (5): 988-93.

IntroductionTimely detection of acute kidney injury (AKI) facilitates prevention of its progress and potentially therapeutic interventions. The study objective is to develop and validate an electronic surveillance tool (AKI sniffer) to detect AKI in 2 independent retrospective cohorts of intensive care unit (ICU) patients. The primary aim is to compare the sensitivity, specificity, and positive and negative predictive values of AKI sniffer performance against a reference standard.MethodsThis study is conducted in the ICUs of a tertiary care center. The derivation cohort study subjects were Olmsted County, MN, residents admitted to all Mayo Clinic ICUs from July 1, 2010, through December 31, 2010, and the validation cohort study subjects were all patients admitted to a Mayo Clinic, Rochester, campus medical/surgical ICU on January 12, 2010, through March 23, 2010. All included records were reviewed by 2 independent investigators who adjudicated AKI using the Acute Kidney Injury Network criteria; disagreements were resolved by a third reviewer. This constituted the reference standard. An electronic algorithm was developed; its precision and reliability were assessed in comparison with the reference standard in 2 separate cohorts, derivation and validation.ResultsOf 1466 screened patients, a total of 944 patients were included in the study: 482 for derivation and 462 for validation. Compared with the reference standard in the validation cohort, the sensitivity and specificity of the AKI sniffer were 88% and 96%, respectively. The Cohen κ (95% confidence interval) agreement between the electronic and the reference standard was 0.84 (0.78-0.89) and 0.85 (0.80-0.90) in the derivation and validation cohorts.ConclusionAcute kidney injury can reliably and accurately be detected electronically in ICU patients. The presented method is applicable for both clinical (decision support) and research (enrollment for clinical trials) settings. Prospective validation is required.Copyright © 2015 Elsevier Inc. All rights reserved.

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