Clinical Chemistry AACC Online Job Center
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Clinical Chemistry 48: 2236-2241, 2002;
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (11)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Penders, J.
Right arrow Articles by Delanghe, J. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Penders, J.
Right arrow Articles by Delanghe, J. R.
Related Collections
Right arrow General Clinical Chemistry
Right arrow Automation and Analytical Techniques
(Clinical Chemistry. 2002;48:2236-2241.)
© 2002 American Association for Clinical Chemistry, Inc.

Quantitative Evaluation of Urinalysis Test Strips

Joris Penders1, Tom Fiers1 and Joris R. Delanghea1

1 Department of Clinical Chemistry University Hospital Ghent, De Pintelaan 185, B-9000 Ghent, Belgium.

aAuthor for correspondence. Fax 32-9-240-4985; e-mail joris.delanghe{at}rug.ac.be.

Background: Urine test strip results are generally reported in categories (i.e., ordinal scaled), but automated strip readers are now available that can report quantitative data. We investigated the possible use of these meters to complement flow cytometry of urine and compared reflectance readings with quantitative determinations of urinary glucose and microalbumin.

Methods: We compared URISYS 2400 (Roche) quantitative reflectance data with data from the UF-100 (Sysmex) and biochemical data for 436 nonpathologic and pathologic urine samples.

Results: Reproducibility of the reflectance signal was good for high- and low-concentration urine pools for protein (0.8% and 0.9% and 1.5% and 2.2% within and between runs, respectively), leukocyte esterase (1.1% and 1.0%; 5.1% and 1.2%), hemoglobin (1.7% and 1.1%; 8.9% and 1.1%) and glucose (2.1% and 0.5%; 6.5% and 2.3%). Fair agreement was obtained between UF-100 and test strip reflectance data for erythrocytes and hemoglobin (r = -0.680) and leukocytes and leukocyte esterase (r = -0.688). Higher correlations were observed for biochemical and test strip data comparing protein and albumin (r = -0.825) and glucose data (r = -0.851). The lower limits of detection for erythrocytes and leukocytes were 8 x 106/L and 19 x 106/L, respectively. The protein test (n = 220) detected 86% (95% confidence interval, 78–92%) of samples with <30 mg/L albumin with a specificity of 84% (95% confidence interval, 76–91%).

Conclusions: In urine test strip analysis, quantitative hemoglobin and leukocyte esterase reflectance data are complementary with flow cytometric results and glucose and albumin results.




The following articles in journals at HighWire Press have cited this article:


Home page
Clin. Chem.Home page
B. Lumbreras-Lacarra, J. M. Ramos-Rincon, and I. Hernandez-Aguado
Methodology in Diagnostic Laboratory Test Research in Clinical Chemistry and Clinical Chemistry and Laboratory Medicine
Clin. Chem., March 1, 2004; 50(3): 530 - 536.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2002 by the American Association for Clinical Chemistry.