Abstract and Introduction
Abstract
Objective: Examination of urine sediment is crucial in acute kidney injury (AKI). In such renal injury, tubular epithelial cells, epithelial cell casts, and dysmorphic red cells may provide clues to etiology. The aim of this study was to compare automated urinalysis findings with manual microscopic analysis in AKI.
Methods: Samples from patients diagnosed with AKI and control patients were included in the study. Red blood cells, white blood cells, renal tubular epithelial cells/small round cells, casts, and pathologic (path) cast counts obtained microscopically and by a UF1000i cytometer were compared by Spearman test. Logistic regression analysis was used to assess the ability to predict AKI from parameters obtained from the UF1000i.
Results: There was poor correlation between manual and automated analysis in AKI. None of the parameters could predict AKI using logistic regression analysis. However, the increment in the automated path cast count increased the odds of AKI 93 times.
Conclusion: Automated urinalysis parameters are poor predictors of AKI, and there is no agreement with manual microscopy.
Introduction
Acute kidney injury (AKI) is encountered in hospitalized and critically ill patients.[1] It results from sudden loss of renal excretory functions and can occur in the context of other illnesses. Etiologies for AKI can be prerenal, intrinsic renal, or postrenal.[1] Microscopic findings in urine from patients with AKI vary from a bland urine sediment with few hyaline casts in prerenal AKI to muddy brown casts, coarse granular casts, epithelial cell casts, and renal tubular epithelial cells (RTEC) in renal AKI. Other findings indicative of glomerular pathology include hematuria, red cell fragments, red cell casts, and white cell casts.[1–3]
Urine microscopy has been extensively studied and scored for prediction of acute tubular necrosis, differentiating septic from aseptic AKI, predicting prognosis, and even predicting dialysis.[4–8] Perazella, Coca, Kanbay, et al[4] identified a scoring system incorporating microscopic findings of granular casts and RTEC to differentiate prerenal AKI from renal AKI. Using this scoring system, they were able to predict a worsening of the stages of AKI. With the advent of automation in urinalysis, automated analyzers based on flow cytometry and digital microscopy have replaced time-consuming microscopic evaluation and reagent strip analysis.[9] Studies have correlated automated analyzers with microscopy, and correlations have varied from 0.49 to 0.96 for the various formed elements in urine.[9–11]
There is limited literature regarding the use of automated urine microscopy in AKI.[12,13] Hence, we undertook this study to evaluate the role of the UF1000i cytometer in predicting AKI and to compare automated urinalysis with manual microscopy in patients with AKI.
Lab Med. 2021;52(2):e30-e38. © 2021 American Society for Clinical Pathology
