Risk Factors for Acute Kidney Injury in Hospitalized Non-Critically Ill Patients: A Population-Based Study.
Mayo Clin Proc. 2020 Mar;95(3):459-467
Authors: Safadi S, Hommos MS, Enders FT, Lieske JC, Kashani KB
OBJECTIVE: To develop and validate an acute kidney injury (AKI) risk prediction model for hospitalized non-critically ill patients.
PATIENTS AND METHODS: We retrospectively identified all Olmsted County, Minnesota, residents admitted to non-intensive care unit (ICU) wards at Mayo Clinic Hospital, Rochester, Minnesota, in 2013 and 2014. The cohort was divided into development and validation sets by year. The primary outcome was hospital-acquired AKI defined by Kidney Disease: Improving Global Outcomes criteria. Cox regression was used to analyze mortality data. Comorbid risk factors for AKI were identified, and a multivariable model was developed and validated.
RESULTS: The development and validation cohorts included 3816 and 3232 adults, respectively. Approximately 10% of patients in both cohorts had AKI, and patients with AKI had an increased risk of death (hazard ratio, 3.62; 95% CI, 2.97-4.43; P<.001). Significant univariate determinants of AKI were preexisting kidney disease, diabetes mellitus, hypertension, heart failure, vascular disease, coagulopathy, pulmonary disease, coronary artery disease, cancer, obesity, liver disease, and weight loss (all P<.05). The final multivariable model included increased baseline serum creatinine value, admission to a medical service, pulmonary disease, diabetes mellitus, kidney disease, cancer, hypertension, and vascular disease. The area under the receiver operating characteristic curves for the development and validation cohorts were 0.71 (95% CI, 0.69-0.75) and 0.75 (95% CI, 0.72-0.78), respectively.
CONCLUSION: Hospital-acquired AKI is common in non-ICU inpatients and is associated with worse outcomes. Patient data at admission can be used to identify increased risk; such patients may benefit from more intensive monitoring and earlier intervention and testing with emerging biomarkers.
PMID: 32008812 [PubMed - in process]