How Reliable Is Automated Urinalysis in Acute Kidney Injury?

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.

journal_name

Lab Med

journal_title

Laboratory medicine

authors

Chandrashekar V,Tarigopula A,Prabhakar V

doi

10.1093/labmed/lmaa069

subject

Has Abstract

pub_date

2020-10-03 00:00:00

eissn

0007-5027

issn

1943-7730

pii

5917569

pub_type

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