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    MODIFIED KDIGO FOR PREDICTING MORTALITY IN ICU PATIENTS RECEIVING CONTINUOUS RENAL REPLACEMENT THERAPY FOR ACUTE RENAL FAILURE: KDIGO-URINARY OUTPUT VS. KDIGO-SERUM CREATININE LEVEL
    (CARBONE EDITORE, 2016) Tulgar, Serkan; Cakiroglu, Basri; Cevik, Banu Eler; Karakilic, Evvah; Ates, Nagihan Gozde; Gergerli, Ruken; Ozdemir, Erman
    Introduction: Acute Renal Injury (ARI) is a constant problem for patients in intensive care and Continuous Renal Replacement Therapy (CRRT) is an ever-more important part of acute renal injury (ARI) treatment. Various criteria have been used for the diagnosis and classification of acute renal failure, including RIFLE (Risk-Injury-Failure-Loss-End stage), AKIN (Acute Kidney Injury Network) and most recently KDIGO (Kidney Disease: Improving Global Outcomes). Many studies have only evaluated urinary output or serum creatinine when categorizing ARI. Our aim was to determine the predictors of mortality in intensive care patients treated with CRRT and to compare mortality with ARI level as determined by KDIGO-Serum Creatinine (KDIGO-SCr) and KDIGO-urinary output (KDIGO-UO) Materials and methods: This retrospective study was performed on intensive care patients receiving CRRT at our institute between January 2010-December 2011. Patient files were reviewed and demographic data, hospitalization time, laboratory findings, CRRT commencement and ARI levels were noted. Results: Seventy patients were included in the study. Mortality was found to be associated with patients' age, Glascow Coma Scale (GCS) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score and adjusted predicted death rate. (p<0,01). Receiver Operating Curve (ROC) area under the curve was statistically significant for determination of mortality using KDIGO-SCR (p<0.01) although the same was not true for KDIGO-UO (p>0.05). Conclusions: We believe that RIFLE, AKIN, KDIGO criteria are each good predictors of mortality. In the case of KDIGO criteria, based solely on serum creatinine or urinary output, KDIGO-SCr was found to be a better predictor of mortality when compared to KDIGO-UO.