Kosin Med J.  2022 Dec;37(4):342-353. 10.7180/kmj.22.144.

Evaluation of automated calibration and quality control processes using the Aptio total laboratory automation system

Affiliations
  • 1Department of Laboratory Medicine, Dong-A University College of Medicine, Busan, Korea
  • 2Kosin University College of Medicine, Busan, Korea
  • 3Department of Laboratory Medicine, Kosin University College of Medicine, Busan, Korea

Abstract

Background
The objective of this study was to determine whether manually performed calibration and quality control (QC) processes could be replaced with an automated laboratory system when installed analyzers fail to provide automated calibration and QC functions.
Methods
Alanine aminotransferase (ALT), total cholesterol (TC), creatinine (Cr), direct bilirubin (DB), and lipase (Lip) items were used as analytes. We prepared pooled serum samples at 10 levels for each test item and divided them into two groups; five for the analytical measurement range (AMR) group and five for the medical decision point (MDP) group. Calibration and QC processes were performed for five consecutive days, and ALT, TC, Cr, DB, and Lip levels were measured in the two groups using automated and manual methods. Precision and the mean difference between the calibration and QC methods were evaluated using the reported values of the test items in each group.
Results
Repeatability and within-laboratory coefficients of variation (CVs) between the automated system and the conventional manual system in the AMR group were similar. However, the mean reported values for test items were significantly different between the two systems. In the MDP group, repeatability and within-laboratory CVs were better with the automation system. All calibration and QC processes were successfully implemented with the Aptio total laboratory automation system.
Conclusion
The Aptio total laboratory automation system could be applied to routine practice to improve precision and efficiency.

Keyword

Automation; Calibration; Quality control; Workflow

Figure

  • Fig. 1. Bland-Altman plot for the analytical measurement range group. The solid line indicates the difference in the mean values of the tested items between an automated system and a conventional manual system. The dotted line indicates the 95% limits of agreement (LoA). Most points on the Bland-Altman plot are scattered within the 95% LoA. Although the majority of points in direct bilirubin (DB) are above the mean line, there seems to be no consistent bias between the values of the two systems. Most points with the lowest values are scattered below the mean line except for lipase (Lip). However, all values are within the 95% LoA. (A) Difference of alanine aminotransferase (ALT). (B) Difference of total cholesterol (TC). (C) Difference of creatinine (Cr). (D) Difference of DB. (E) Difference of Lip.

  • Fig. 2. Bland-Altman plot for the medical decision point group. The solid line indicates the difference in the mean values of the tested items between an automated system and a conventional manual system. Most points on the Bland-Altman plot are scattered within the 95% limits of agreement (LoA). There seems to be no consistent bias between the values of the two systems. (A) Difference of alanine aminotransferase (ALT). (B) Difference of total cholesterol (TC). (C) Difference of creatinine (Cr). (D) Difference of direct bilirubin (DB). (E) Difference of lipase (Lip).

  • Fig. 3. Bland-Altman plot for quality control materials. The solid line indicates the difference in the mean values of the tested items between an automated system and a conventional manual system. Most points on the Bland-Altman plot are scattered within the 95% limits of agreement (LoA). There seems to be no consistent bias between the values of the two systems. (A) Difference of alanine aminotransferase (ALT). (B) Difference of total cholesterol (TC). (C) Difference of creatinine (Cr). (D) Difference of direct bilirubin (DB). (E) Difference of lipase (Lip).


Reference

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