ABSTRACT
In this study, we investigated the effects of severe hemolysis (hemoglobin [Hb] > 500 mg/dL) in blood specimens by classifying them into non-hemolysis, hemolysis (Hb ≤ 500 mg/dL), and severe hemolysis. Investigated items were total protein (TP), albumin (ALB), total bilirubin (T-Bil), direct bilirubin (D-Bil), aspartate transaminase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LD), alkaline phosphatase (ALP), gamma-glutamyl transferase (γ-GT), creatine kinase (CK), amylase (AMY), cholinesterase (ChE), blood urea nitrogen (BUN), creatinine (Cre), sodium (Na), potassium (K), chloride (Cl), calcium (Ca), uric acid (UA), triglycerides (TG), total cholesterol (T-Cho), high-density lipoprotein cholesterol (HDL-C), lowdensity lipoprotein cholesterol (LDL-C), and C-reactive protein (CRP), and actual clinical test results were used. Based on the results, we were able to classify the error relationships into three groups according to hemolysis status. Group A shows an error between non-hemolysis and hemolysis, and an even stronger error in severe hemolysis (T-Bil, AST, LD, Na, K, Ca, and UA). Group B showed no error between non-hemolysis and hemolysis, but errors in strong hemolysis (ALB, D-Bil, ALT, γ-GT, CK, AMY, TG, T-Cho, HDL-C, and LDL-C). Group C shows no errors in either hemolysis or strong hemolysis (TP, ALP, ChE, BUN, Cre, Cl, and CRP). Among these, the Group B classification was a new finding. In situations where the measurement of hemolyzed specimens is unavoidable, it is important that clinical laboratory technologists be aware of its impact and provide the results in a way that can be used in clinical practice.
ABSTRACT
The platelet counts documented in most of the studies using the fully automated hematology analyzer XE-5000 are values measured by impedance technology (PLT-I). If blood specimens showing an anomalous particle-size distribution curve in the area where platelet counts are low are used (exceptionally low platelet count samples), the counting method is automatically switched over to an optical method (PLT-O). In the present study, we examined the usefulness of the XE-5000 by comparing PLT-I with PLT-O, using blood samples with low platelet counts collected from patients who visited our hospital between January 1 and March 31, 2012. Dilution linearity left nothing to be desired in either of the two, but simultaneous reproducibility was higher in PLT-O than in PLT-I. The correlations of PLT-I and PLT-O with visual counts were high, working out at r＝0.889～0.984. In the exceptionally low platelet count samples, the correlation coefficient was high in PLT-O than in PLT-I. The cases showing low platelet counts frequently presented giant platelets and/or red cell fragments. Therefore, measuring the samples with low platelet counts requires a high degree of precision. In the samples with exceptionally low platelet counts, PLT-O exceeded PLT-I in simultaneous reproducibility and correlation with visual counts. Thus, our study demonstrated the usefulness of the XE-5000 that could enumerate PLT-O automatically and speedily.