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Acute Kidney Injury Risk Factors for Icu Patients Following Cardiac Surgery: The Application of Joint Modeling Publisher



Khoundabi B1 ; Kazemnejad A1 ; Mansourian M2 ; Hashemian SM3 ; Dizaji MK1
Authors
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Authors Affiliations
  1. 1. Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, IR, Iran
  2. 2. Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, IR, Iran
  3. 3. Critical Care Chronic Respiratory Disease Research Center (CRDRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, IR, Iran

Source: Trauma Monthly Published:2016


Abstract

Background: Admission to the ICU (intensive care unit) is frequently complicated by early AKI (acute kidney injury). The developmen of AKI following cardiac surgery is particularly associated with increased mortality and morbidity. According to AKIN (acut kidney injury network) criteria, UO (urinary output) is a predictor for AKI Objectives: The goal of this study was to determine the effects of some AKI risk factors on AKI and also to investigate changes in U as a predictor of AKI using joint modeling Patients and Methods: In a retrospective study, 300 cardiac-operated patients, whohad been admitted over a period of three years were selected according to the consecutive sample selection method, using the ICU at Masih Daneshvari Hospital in Iran as a referra center. The random mixed effect model and the survival model were used to investigate UO changes and estimate the effect of U and other risk factors on the hazard rate of AKI in a joint analysis Results: AKI occurred in 38.0% of patients. A significant decrease of UO occurred more often in female and infected patients, a well as those with a low DBP (diastolic blood pressure). The survival model showed that the risk of AKI in females, older patients an patients with low DBP, lowerUOand with infection was higher (P = 0.001). Using joint modeling, the association parameter betwee the risk of AKI and UO was estimated (-0.3, P = 0.002) Conclusions: Where there is a relationship between two longitudinal and survival responses, joint modeling can estimate it.
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