Abstract
This study evaluated the diagnostic value of the automated UF-5000 parameters and compared it with that of aberrant erythrocytes and acanthocytes classified by microscopy for identifying IgA glomerular hematuria to propose a predictive model for clinical use. It also compared correlations between erythrocyte parameters and malformed erythrocytes. Urine samples from 53 biopsy-proven IgA hematuria cases and 143 non-IGA nephropathic hematuria cases as controls were analyzed. The ratio of small red blood cells to nonlysed red blood cells (UF-sRBC%) and lysed red blood cells (lysed RBCs) showed good diagnostic performance for IgA glomerular hematuria (area under the curve [AUC] = 0.857 [P = 0.000] and AUC = 0.860 [P = 0.000], respectively). Combining UF-sRBC%, lysed RBCs, and urine protein dry chemistry improved the diagnostic accuracy (AUC = 0.967; positive predictive value [PPV] = 91.89%; negative predictive value [NPV] = 93.10%; P = 0.000). This approach surpassed traditional microscopy for aberrant erythrocytes (AUC = 0.895; PPV = 62.27%; NPV = 88.66%; P = 0.008) and acanthocytes (AUC = 0.868; PPV = 72.97%; NPV = 83.65%; P = 0.006). The erythrocyte size index was negatively correlated with the proportion of urinary aberrant erythrocytes (r = - 0.787; P = 0.000). The UF-5000 erythrocyte parameters facilitate rapid identification of IgA nephropathy and could replace manual microscopy.