Adil Ahmed1, Srinivasan Vairavan2, Abbasali Akhoundi3, Gregory Wilson4, Caitlyn Chiofolo2, Nicolas Chbat2, Rodrigo Cartin-Ceba4, Guangxi Li4, Kianoush Kashani5. 1. 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. 2. Philips Research North America, Briarcliff Manor, NY. 3. Department of Anesthesiology, Shahid Beheshti University, Tehran, Iran. 4. Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN. 5. Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN. Electronic address: kashani.kianoush@mayo.edu.
Abstract
INTRODUCTION: Timely 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. METHODS: This 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. RESULTS: Of 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. CONCLUSION: Acute 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.
INTRODUCTION: Timely 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. METHODS: This 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. RESULTS: Of 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. CONCLUSION:Acute 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.
Authors: Sami Safadi; Musab S Hommos; Felicity T Enders; John C Lieske; Kianoush B Kashani Journal: Mayo Clin Proc Date: 2020-01-31 Impact factor: 7.616
Authors: Kianoush Kashani; Min Shao; Guangxi Li; Amy W Williams; Andrew D Rule; Walter K Kremers; Michael Malinchoc; Ognjen Gajic; John C Lieske Journal: Kidney Int Date: 2017-05-18 Impact factor: 10.612
Authors: Hilary R Teaford; Andrew D Rule; Kristin C Mara; Kianoush B Kashani; John C Lieske; Diana J Schreier; Patrick M Wieruszewski; Erin F Barreto Journal: Mayo Clin Proc Date: 2020-08 Impact factor: 7.616
Authors: Diana J Schreier; Kianoush B Kashani; Ankit Sakhuja; Kristin C Mara; Mohammad S Tootooni; Heather A Personett; Sarah Nelson; Andrew D Rule; James M Steckelberg; Aaron J Tande; Erin F Barreto Journal: Clin Infect Dis Date: 2019-04-24 Impact factor: 9.079
Authors: Marcin A Pachucki; Erina Ghosh; Larry Eshelman; Krishnamoorthy Palanisamy; Timothy Gould; Matthew Thomas; Chris P Bourdeaux Journal: J Intensive Care Soc Date: 2018-04-30