Introduction Purpose Body mass index (BMI) is calculated using height and weight, this is a simple and useful index for nutrition and obesity. Furthermore,

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Introduction Purpose Body mass index (BMI) is calculated using height and weight, this is a simple and useful index for nutrition and obesity. Furthermore, BMI has been known as a prognostic factor in many medical conditions. In chronic obstructive pulmonary disease, chronic renal failure and cancer, mortality increase in underweight patients. And in metabolic syndrome, such as hypertension, diabetes mellitus and dyslipidemia, mortality increase in overweight patients. Therefore, general population has ‘J’ or ‘U’-shaped relationship between BMI and mortality. Many studies have been conducted whether BMI is a useful prognostic factor in critically ill patients. However, these studies have shown heterogeneous results. Mortality increased in morbid obesity, however, no relation was proved in prospective study. Moreover, recent studies have shown ‘obesity paradox’, that is, mortality in ICU is lower in obese patients than in underweight patients. Acute kidney injury (AKI) is a common medical condition at the time of admission and severe complication of critically ill patients. It affects prognosis of patients who admit ICU. Mortality is higher and hospital stay is longer in the patients with AKI. However, there have been little studies about that. The relationship between obesity and AKI is uncertain in critically ill patients. In this study, we hypothesized that AKI occurs less frequently in obese patients in critically ill condition. Body mass index as a predictor of acute kidney injury in critically ill patients Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea Ho Cheol Kim, Jung-Wan Yoo, Seung Jun Lee, Yu Ji Cho, Yi Yeong Jeong, Jong Deog Lee Body mass index as a predictor of acute kidney injury in critically ill patients Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea Ho Cheol Kim, Jung-Wan Yoo, Seung Jun Lee, Yu Ji Cho, Yi Yeong Jeong, Jong Deog Lee Methods This retrospective study was conducted in a 13-bed MICU of an 869-bed tertiary care hospital in Korea. All patients admitted to the medical intensive care unit (MICU) from December 2011 to May 2014, were eligible for the study. Patients were excluded if they were admitted for acute coronary syndrome, overdoses, or < 18 years old. Data were collected for each patient at admission to MICU and discharge from MICU by MICU registry in our institution. Demographic information, past medical history and reasons for ICU admission were collected. The Acute Physiology and Chronic Health Evaluation (APACHE) II score and the Sequential Organ Failure Assessment (SOFA) score were calculated as a measure of severity of illness and as a predictor of mortality. Body weight and height were measured and recorded on ICU admission. BMI was calculated as body weight, kg/height, m 2. The degree of obesity was classified into 3 groups: underweight, BMI < 18.5 kg/m 2 ; normal, BMI kg/m 2 ; and overweight/obese ≥ 25.0 kg/m 2. AKI was defined by the Risk Injury Failure Loss and End-stage kidney disease (RIFLE) criteria using creatinine, glomerular filtration rate (GFR) and urine output[13]. The number of days the patient required mechanical ventilation, length of stay (LOS) in MICU and hospital, and mortality in MICU and hospital were assessed. Continuous variables are reported as the mean ± SD. Categorical variables were described as No. (%). Difference testing between the groups was performed using analysis of variance (ANOVA), Student’s t test, or chi-squared test, as appropriate. Logistic regression analysis was performed to examine BMI and AKI occurrence. A p values of < 0.05 were considered statistical significant for all tests. All data were analyzed using the SPSS version 18.0 for Window (SPSS Inc., Chicago, IL, USA). Results Discussion BMI is a possible predictor of AKI in ICU patients, as this study indicated that AKI occurs more frequently in overweight patients than in underweight patients. The purpose of this study was to assess the association between AKI and obesity in critically ill patients. Conclusion Higher BMI is risk factor for development of AKI in critically ill patients in this study. This result can be explained with following mechanism. First, in obese people, there are some hemodynamic glomerular change like glomerular hyperperfusion and hyperfiltrtation. This hemodynamic change can be explained with impaired natriuresis associated activation of renin, angiotensin activation system, which cause vasodilation of glomerular arteriole and subsequent transmission to increased pressure to glomerular capillary. Second, because of obesity to increased hemodynamic and metabolic load to individual glomerular resulting low number of functional nephron in obese subject. Low functional nephron is associated with glomerular hypertrophy and increased capillary pressure of remaining functional nephron which is associated with glomerulosclerosis. Third, adipocyte in obese subjects is production site of activated inflammatory cytokine and oxidative stress. The loss of redox homeostasis contributes to renal remodeling, which is a structural rearranging adaptive process that occurs long-term, as a chronic response to injurious stimuli. These proposed mechanism for relation between obesity and kidney injury is strongly supported that reduction of body weight in obese type II diabetes subjects is associated with significant decrease of proteinuria. These underlying mechanism may explained to be vulnerable to renal injury in critically ill patients. Despite of high occurrence of AKI in high BMI patients, the mortality rate was no significantly different between each BMI group. Several studies showed that high BMI is usually associated with probability of survival in patients with critical illness. So, no differences of mortality in BMI with AKI were compensated by the difference of the mortality according to BMI group. There are some limitations of this study. First, the patients were enrolled in medical ICU of single tertiary hospital. The risk factors of AKI in medical ICU and surgical ICU may be quite different. In surgical ICU patients, the risk factors usually occur in postoperative state which is associated with volume status. In contrast, in medical ICU patients, various risk factor like infection, medication like contract or antibiotics, are also existed. According to patients underlying status and cause, risk of AKI and outcome may be quite different. Second, the enrolled patients characteristics was heterogeneous. It is more valuable to assess risk factor of AKI in homogenous group of patients like sepsis or lung injury.