Authors
SERKAN TULGAR1*, BASRI CAKIROGLU2
, BANU ELER CEVIK3
, EVVAH KARAKILIC4
, NAGIHAN GOZDE ATES5
, RUKEN GERGERLI6
,
ERMAN OZDEMIR7
Departments
1
Consultant of Anesthesiology & Reanimation, Pendik State Hospital, Department of Anesthesiology, Istanbul, Turkey - 2
Consultant
of Urology, Hisar Intercontinental Hospital, Department of Urology, Istanbul, Turkey - 3
Consultant of Anesthesiology &
Reanimation, Dr. Lutfi Kirdar Education & Research Hospital, Department of Anesthesiology, Istanbul, Turkey - 4
Consultant of
Emergency, Ankara Numune Training & Research Hospital, Department of Emergency, Ankara, Turkey - 5
Consultant of
Anesthesiology & Reanimation, Gumushane State Hospital, Department of Anesthesiology, Gumushane, Turkey - 6
Consultant of
Anesthesiology & Reanimation, Karakocan State Hospital, Department of Anesthesiology, Elazig, Turkey - 7
Consultant of
Nephrology, Dr. Lutfi Kirdar Education & Research Hospital, Department of Nephrology, Istanbul, Turkey
Abstract
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
Keywords
KDİGO, Acute Renal Injury, Critical Care, Creatinine
DOI:
10.19193/0393-6384_2016_3_88