Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Department of Epidemiology and Biostatistics, School of Public Health , Isfahan University of Medical Sciences, Isfahan, Iran
Mycobacteriology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran,
Chronic Respiratory Disease Research Center(CRDRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Background: Admission to the intensive care unit (ICU) is often complicated by early acute kidney injury (AKI). AKI is associated with high rates of mortality and morbidity. Risk factors and incidence of AKI have been notably high following non-cardiac surgery in the past decade. The aim of this study was to determine the hazard rate of AKI, the effect of risk factors of AKI and also to assess the changes in urine output (UO) as a predictor of AKI using joint modeling in patients undergoing non-cardiac surgery. Materials and Methods: In this retrospective cohort study, 400 non-cardiacoperated patients admitted during 3 years to the ICU of Masih Daneshvari Hospital were selected according to the consecutive sample selection method. Random mixed effect model and survival model were used to assess UO changes and the effect of UO and other risk factors on the hazard rate of AKI using joint analysis. Results: AKI occurred in 8.8% of the Iranian non-cardiac-operated patients. Survival model showed that the risk of AKI in lower diastolic blood pressure (DBP), higher Acute Physiology and Chronic Health Evaluation II score (APACHE II score), emergency surgery, longer hospitalization and male patients was higher (P=0.001). Using joint modeling, an association was found between the risk of AKI and UO (-0.19, P=0.002). Conclusion: Several predictors were found to be associated with AKI in the Iranian patients after non-cardiac surgery. A relationship between longitudinal and survival responses was found in this study and joint modeling caused considerable improvement in estimations compared to separate longitudinal and survival models.