ASSOCIATION OF URINARY SEDIMENTS SCORE WITH THE SEVERITY AND DIFFERENT TYPE OF ACUTE KIDNEY INJURY (AKI) IN HOSPITALIZED PATIENTS

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ASSOCIATION OF URINARY SEDIMENTS SCORE WITH THE SEVERITY AND DIFFERENT TYPE OF ACUTE KIDNEY INJURY (AKI) IN HOSPITALIZED PATIENTS
MD AJFAR SAZID
KHAN
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Urinary microscopic examination of acute kidney injury patients is an important diagnostic tool for the detection of severity and different type of AKI. The purpose of the present study was to find out relation between urinary sediment scoring and different stages of acute kidney injury (AKI) according to AKIN in hospitalized patients.

This cross sectional study was conducted over a period of one and half (1.5) years in the Department of Nephrology at Bangabandhu Sheikh Mujib Medical University, Dhaka. All acute kidney injury (AKI) patients more than 18 years of age with both sexes fulfilling the inclusion criteria were included in the study. Fresh urine were obtained from the patients and were examined within 1 hour after voiding. A urinary sediment scoring system was created on the basis of the number of renal tubular epithelial cells and granular casts. The primary outcome was worsening of AKI 

Of 75 patients consulted for AKI, 68 had acute tubular necrosis and 7 had pre renal AKI and were included in the analysis. At consultation, 20 (26.7%) had stage 1, 29 (38.7%) had stage 2, and 26 (34.6%) had stage 3 AKI according to AKIN stages.(Fig: 1). The urinary sediment combined scores were lowest in those with stage 1 and highest in stage 3 ( Table 1) . A strong positive spearman correlation was found between combined urinary sediment score and AKIN stage, (Fig: 2). Pre renal AKI patients scored low whereas ATN patients scored high according to combined urinary sediment score. A strong positive correlation was found between combined urinary sediment score and different type of AKI.

The urinary sediment score is associated with the AKIN stages of AKI at the time of renal consultation and it is a useful tool to predict the severity & type of AKI during hospitalization.

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