A novel semi-automated method for urine protein assay associated with calculation of sigma metric

Authors

  • Reza Pahlavan Gharehbaba Department of Biochemistry and Clinical Laboratories, Tabriz University of Medical Science, Tabriz, Iran
  • Zahra Mehrabi Department of Clinical Chemistry, 9th Dey Manzariyeh Hospital, Isfahan, Iran
  • Seyed Mohammad Masoodian Department of Medical Laboratory Science, School of Allied Medical Science, Student Research Committee, Shahid Beheshti University of Medical Science, Tehran, Iran

Keywords:

Urine protein, Quality control, CLSI, Total error, Sigma metric, IVD

Abstract

Introduction: a novel semi-automated method for urine protein assay was introduced, validated and also analytical performance evaluation was conducted for the clinical laboratories practice. Materials and method: Introduced method was calibrated based on multipoint calibration with human based biochemistry calibrator. All of the method validation procedure was done according to the CLSI guidance. Finally, total error, sigma metric and performance of quality was evaluated. Results: Results indicate the good correlation with Biuret and pyrogallol-red methods in ranging from 0.33 to 6760 mg/dl. Method was linear up to 6760 mg/dl and was highly sensitive compared to pyrogallol-red method. Based on sigma scale, introduced method have good performance in broad measuring range and based on comparison practice, sigma was >6 in all decision levels for urine protein concentration. Conclusion: In conclusion, novel semi-automated method can be selected as preferred method in reference laboratory. Also, IVD manufacturers can use sigma scale results to improve diagnostic products.

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Published

2021-04-01

How to Cite

Reza Pahlavan Gharehbaba, Zahra Mehrabi, & Seyed Mohammad Masoodian. (2021). A novel semi-automated method for urine protein assay associated with calculation of sigma metric. World Journal of Pharmaceutical Sciences, 9(4), 15–28. Retrieved from https://wjpsonline.com/index.php/wjps/article/view/100

Issue

Section

Research Article